American Health And Drug Benefits September 2011 Vol 4 No5

THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™ SEPTEMBER 2011

VOLUME 4, NUMBER 5

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

Theme Issue

CARDIOMETABOLIC HEALTH AND WELLNESS Introduction: In Search of Stakeholder Collaboration to Stem the Cardiometabolic Epidemic Obesity in the Workplace: Impact on Cardiovascular Disease, Cost, and Utilization of Care ™

Alberto M. Colombi, MD, MPH; G. Craig Wood, MS

Stakeholder Perspective by Wayne M. Lednar, MD, PhD

A Call to Action: Responding to the Future Forecasting of Cardiovascular Disease in America Robert Lee Page II, PharmD, MSPH, FAHA, FCCP, FASCP, FASHP, BCPS (AQ cards); Vahram Ghushchyan, PhD; Kavita Nair, PhD

Stakeholder Perspective by James T. Kenney, RPh, MBA

Atypical Antipsychotics and Metabolic Syndrome in Patients with Schizophrenia: Risk Factors, Monitoring, and Healthcare Implications Henry J. Riordan, PhD; Paola Antonini, MD, PhD; Michael F. Murphy, MD, PhD

Stakeholder Perspective by Atheer A. Kaddis, PharmD

Current Therapies and Emerging Drugs in the Pipeline for Type 2 Diabetes Quang T. Nguyen, DO; Karmella T. Thomas, BS, RD; Katie B. Lyons, MS II; Loida D. Nguyen, PharmD, BCBS; Raymond A. Plodkowski, MD

Stakeholder Perspective by James V. Felicetta, MD

Lipid Management in Patients with Type 2 Diabetes Marsha J. Daniel, PharmD, cPh, CDE

Stakeholder Perspective by Gary M. Owens, MD

©2011 Engage Healthcare Communications, LLC www.AHDBonline.com

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April 2011

EDITORIAL BOARD

CLINICAL EDITOR

HEALTH INFORMATION TECHNOLOGY

PHARMACY BENEFIT DESIGN

Thomas G. McCarter, MD, FACP Chief Clinical Officer Executive Health Resources, PA

J. B. Jones, PhD, MBA Research Associate, Geisinger Health System, Danville, PA

Joel V. Brill, MD Chief Medical Officer, Predictive Health, Phoenix, AZ

GOVERNMENT EDITOR

Victor J. Strecher, PhD, MPH Professor and Director, Center for Health Communications Research University of Michigan Schools of Public Health and Medicine, Ann Arbor Founder and Chief Visionary Officer HealthMedia, Johnson & Johnson

William J. Cardarelli, PharmD Director of Pharmacy, Atrius Health Harvard Vanguard Medical Associates

Kevin B. “Kip” Piper, MA, FACHE President, Health Results Group Sr. Counselor, Fleishman-Hillard Washington, DC ACTUARY

David Williams Milliman Health Consultant Windsor, CT AGING AND WELLNESS

Eric G. Tangalos, MD, FACP, AGSF Professor of Medicine Mayo Clinic, Rochester, MN CANCER RESEARCH

Al B. Benson, III, MD, FACP Professor of Medicine Associate Director for Clinical Investigations Robert H. Lurie Comprehensive Cancer Center, Northwestern University Immediate Past President, ACCC Past Chair, NCCN Board of Directors Samuel M. Silver, MD, PhD, FACP Professor, Internal Medicine Director, Cancer Center Network Division of Hematology/Oncology Assistant Dean for Research University of Michigan Health Systems CARDIOLOGY RESEARCH

HEALTH OUTCOMES RESEARCH

Diana Brixner, RPh, PhD Professor and Chair Department of Pharmacotherapy Executive Director, Outcomes Research Center, University of Utah College of Pharmacy, Salt Lake City Gordon M. Cummins, MS Director, IntegriChain Kavita V. Nair, PhD Associate Professor, School of Pharmacy University of Colorado at Denver Gary M. Owens, MD President, Gary Owens Associates Glen Mills, PA Timothy S. Regan, BPharm, RPh Executive Director, Xcenda Palm Harbor, FL HEALTH & VALUE PROMOTION

Albert Tzeel, MD, MHSA, FACPE National Medical Director HumanaOne, Milwaukee

Michael A. Weber, MD Professor of Medicine Department of Medicine (Cardiology) State University of New York

Sharad Mansukani, MD Chief Strategic Officer, Nations Health Senior Advisor, Texas Pacific Group, FL

ENDOCRINOLOGY RESEARCH

MANAGED MARKETS

James V. Felicetta, MD Chairman, Dept. of Medicine Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ

MANAGED CARE & GOVERNMENT AFFAIRS

EMPLOYERS

Jeffrey A. Bourret, RPh, MS, FASHP Senior Director, Branded Specialty Pharmacy Programs, US Specialty Customers, Pfizer, Specialty Care Business Unit, PA

Alberto M. Colombi, MD, MPH Corporate Medical Director PPG Industries, Pittsburgh, PA

Charles E. Collins, Jr, MS, MBA Vice President, Managed Markets Strategy Fusion Medical Communications

Wayne M. Lednar, MD, PhD Global Chief Medical Officer Director, Integrated Health Services DuPont, Wilmington, DE

PATIENT ADVOCACY

Arthur F. Shinn, PharmD, FASCP President, Managed Pharmacy Consultants, Lake Worth, FL F. Randy Vogenberg, RPh, PhD Principal, Institute of Integrated Healthcare Sharon, MA

William E. Fassett, BSPharm, MBA, PhD Professor of Pharmacy Law & Ethics Vice Chair, Dept. of Pharmacotherapy College of Pharmacy, Washington State University, Spokane, WA PERSONALIZED MEDICINE

Wayne A. Rosenkrans, Jr, PhD Chairman and President, Personalized Medicine Coalition, Distinguished Fellow, MIT Center for Biomedical Innovation

EPIDEMIOLOGY RESEARCH

Joshua N. Liberman, PhD Vice President, Research Operations Center for Health Research Geisinger Health System, Danville, PA

Vol 4, No 5

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September 2011

PHARMACOECONOMICS

Jeff Jianfei Guo, BPharm, MS, PhD Associate Professor of Pharmacoeconomics & Pharmacoepidemiology, College of Pharmacy, University of Cincinnati Medical Center, OH

www.AHDBonline.com

Leslie S. Fish, PharmD Sr. Director of Pharmacy Services Fallon Community Health Plan, MA Michael S. Jacobs, RPh National Clinical Practice Leader Buck Consultants, Atlanta Matthew Mitchell, PharmD, MBA Manager, Pharmacy Services SelectHealth, Salt Lake City, UT Paul Anthony Polansky, BSPharm, MBA Senior Field Scientist, Health Outcomes and PharmacoEconomics (HOPE) Endo Pharmaceuticals, Chadds Ford, PA Scott R. Taylor, RPh, MBA Associate Director, Industry Relations Geisinger Health System, Danville, PA POLICY & PUBLIC HEALTH

Joseph R. Antos, PhD Wilson H. Taylor Scholar in Health Care Retirement Policy American Enterprise Institute Jack E. Fincham, PhD, RPh Professor of Pharmacy, School of Pharmacy University of Missouri, Kansas City Walid F. Gellad, MD, MPH Assistant Professor of Medicine, University of Pittsburgh, Staff Physician, Pittsburgh VA Medical Center, Associate Scientist, RAND Health Alex Hathaway, MD, MPH, FACPM President & Founder, J.D. BioEdge Health quality & biomedical research J. Warren Salmon, PhD Professor of Health Policy & Administration School of Public Health University of Illinois at Chicago RESEARCH & DEVELOPMENT

Michael F. Murphy, MD, PhD Chief Medical Officer and Scientific Officer Worldwide Clinical Trials Faculty, Center for Experimental Pharmacology and Therapeutics, HarvardMIT Division of Health Sciences and Technology, Cambridge, MA SPECIALTY PHARMACY

Atheer A. Kaddis, PharmD Vice President, Managed Markets Diplomat Specialty Pharmacy, Swartz Creek, MI James T. Kenney, RPh, MBA Pharmacy Operations Manager Harvard Pilgrim Health Care, Wellesley, MA

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SEPTEMBER 2011

VOLUME 4, NUMBER 5 THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™

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FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

TABLE OF CONTENTS INTRODUCTION

270 In Search of Stakeholder Collaboration to Stem the Cardiometabolic Epidemic Dalia Buffery, MA, ABD BUSINESS

271 Obesity in the Workplace: Impact on Cardiovascular Disease, Cost, and Utilization of Care Alberto M. Colombi, MD, MPH; G. Craig Wood, MS 278 Stakeholder Perspective by Wayne M. Lednar, MD, PhD CLINICAL

280 A Call to Action: Responding to the Future Forecasting of Cardiovascular Disease in America Robert Lee Page II, PharmD, MSPH, FAHA, FCCP, FASCP, FASHP, BCPS (AQ cards); Vahram Ghushchyan, PhD; Kavita Nair, PhD 287 Stakeholder Perspective by James T. Kenney, RPh, MBA

292 Atypical Antipsychotics and Metabolic Syndrome in Patients with Schizophrenia: Risk Factors, Monitoring, and Healthcare Implications Henry J. Riordan, PhD; Paola Antonini, MD, PhD; Michael F. Murphy, MD, PhD 301 Stakeholder Perspective by Atheer A. Kaddis, PharmD Continued on page 268

American Health & Drug Benefits is included in the following indexing and database services: EMBASE/Elsevier Bibliographic Database SCOPUS/Elsevier Bibliographic Database Cumulative Index to Nursing and Allied Health Literature (CINAHL) EBSCO research databases Standard Periodical Directory MEMBER: Committee on Publication Ethics (COPE) BPA Worldwide membership applied for August 2010.

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Publisher Nicholas Englezos nick@engagehc.com 732-992-1884 Associate Publisher Maurice Nogueira maurice@engagehc.com 732-992-1895 Editorial Director Dalia Buffery dalia@AHDBonline.com 732-992-1889 Director of Client Services Mark Timko 732-992-1897 Associate Editors Brett Kaplan brett@engagehc.com Lara J. Lorton lara@engagehc.com 732-992-1892 Editorial Assistant Jessica A. Smith Senior Production Manager Lynn Hamilton Quality Control Director Barbara Marino Business Manager Blanche Marchitto Founding Editor-in-Chief Robert E. Henry rhenry@AHDBonline.com

Mission Statement American Health & Drug Benefits is founded on the concept that health and drug benefits have undergone a transformation: the econometric value of a drug is of equal importance to clinical outcomes as it is to serving as the basis for securing coverage in formularies and benefit designs. Because benefit designs are greatly affected by clinical, business, and policy conditions, this journal offers a forum for stakeholder integration and collaboration toward the improvement of healthcare.

This publication further provides benefit design decision makers the integrated industry information they require to devise formularies and benefit designs that stand up to today’s special healthcare delivery and business needs.

Contact Information: For subscription information and editorial queries, please contact: editorial@AHDBonline.com T: 732-992-1892 F: 732-992-1881

September 2011

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Vol 4, No 5

moving millimeters

See how many millimeters you can move with EDARBI EDARBI 80 mg was statistically superior to DIOVAN® 320 mg and BENICAR® 40 mg in reducing 24-hr mean ambulatory and clinic SBP1 REDUCTIONS IN 24-HR MEAN AMBULATORY SBP AT WEEK 61,2 Mean ambulatory baseline: Study 1=144.9 mm Hg

▼ Similar results were observed across two other comparator studies: Study 2 vs BENICAR 40 mg and Study 3 vs DIOVAN 320 mg

STUDY 1

▼ Clinic SBP differences between EDARBI and active comparators were consistent with mean ambulatory results Study 1 Design: A 6-week, randomized, double-blind, placebo-controlled, forced-titration study in patients (N = 1,291) with clinic SBP ≥150 mm Hg and ≤180 mm Hg and 24-hr mean SBP ≥130 mm Hg and ≤170 mm Hg. The primary endpoint was change in 24-hr mean ambulatory SBP. Placebo lowered 24-hr mean ambulatory SBP by 0.3 mm Hg. Data shown are placebo corrected.

IMPORTANT SAFETY INFORMATION WARNING: AVOID USE IN PREGNANCY When pregnancy is detected, discontinue EDARBI as soon as possible. Drugs that act directly on the renin-angiotensin system can cause injury and death to the developing fetus. ▼ Avoid fetal or neonatal exposure.

DIOVAN 320 mg

-10.0 mm Hg BENICAR 40 mg

-11.7 mm Hg EDARBI 80 mg

-14.3 mm Hg P<0.001 vs DIOVAN 320 mg P=0.009 vs BENICAR 40 mg References: 1. EDARBI Prescribing Information. 2. White WB, Weber MA, Sica D, et al. Effects of the angiotensin receptor blocker azilsartan medoxomil versus olmesartan and valsartan on ambulatory and clinic blood pressure in patients with stages 1 and 2 hypertension.

Hypertension. 2011;57:413-420.

▼ Correct volume or salt depletion prior to administration of EDARBI. ▼ Monitor for worsening renal function in patients with renal impairment. ▼ In patients with an activated renin-angiotensin system, as by volume or salt depletion, reninangiotensin-aldosterone system (RAAS) blockers such as azilsartan medoxomil can cause excessive hypotension. In patients whose renal function may depend on the activity of the reninangiotensin system, e.g., with renal artery stenosis, treatment with RAAS blockers has been associated with oliguria or progressive azotemia and rarely with acute renal failure and death. ▼ Monitor renal function periodically in patients receiving EDARBI and NSAIDs who are also elderly, volume-depleted, or who have compromised renal function. ▼ The most common adverse reaction in adults was diarrhea (2%).

For further information, please see adjacent Brief Summary of Prescribing Information.

INDICATIONS AND USAGE EDARBI is an angiotensin II receptor blocker indicated for the treatment of hypertension in adults to lower blood pressure. Lowering blood pressure reduces the risk of fatal and nonfatal cardiovascular events, primarily strokes and myocardial infarctions. There are no controlled trials demonstrating risk reduction with EDARBI, but at least one pharmacologically similar drug has demonstrated such benefits.

Control of high blood pressure should be part of comprehensive cardiovascular risk management, including, as appropriate, lipid control, diabetes management, antithrombotic therapy, smoking cessation, exercise, and limited sodium intake. Many patients will require more than one drug to achieve blood pressure goals. EDARBI may be used either alone or in combination with other antihypertensive agents.

EDARBI is a trademark of Takeda Pharmaceutical Company Limited registered with the U.S. Patent and Trademark Office and used under license by Takeda Pharmaceuticals America, Inc.

Trademarks are the property of their respective owners. ©2011 Takeda Pharmaceuticals North America, Inc. All rights reserved. LXA-00482 09/11

BRIEF SUMMARY OF FULL PRESCRIBING INFORMATION for Edarbi (azilsartan medoxomil) tablets WARNING: AVOID USE IN PREGNANCY When pregnancy is detected, discontinue Edarbi as soon as possible.

Drugs that act directly on the renin-angiotensin system can cause injury and death to the developing fetus.

INDICATIONS AND USAGE Edarbi is an angiotensin II receptor blocker (ARB) indicated for the treatment of hypertension to lower blood pressure. Lowering blood pressure reduces the risk of fatal and nonfatal cardiovascular events, primarily strokes and myocardial infarctions. These benefits have been seen in controlled trials of antihypertensive drugs from a wide variety of pharmacologic classes, including the class to which this drug principally belongs. There are no controlled trials demonstrating risk reduction with Edarbi.

Control of high blood pressure should be part of comprehensive cardiovascular risk management, including, as appropriate, lipid control, diabetes management, antithrombotic therapy, smoking cessation, exercise, and limited sodium intake. Many patients will require more than one drug to achieve blood pressure goals. For specific advice on goals and management, see published guidelines, such as those of the National High Blood Pressure Education Programâ&#x20AC;&#x2122;s Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC).

Numerous antihypertensive drugs, from a variety of pharmacologic classes and with different mechanisms of action, have been shown in randomized controlled trials to reduce cardiovascular morbidity and mortality, and it can be concluded that it is blood pressure reduction, and not some other pharmacologic property of the drugs, that is largely responsible for those benefits. The largest and most consistent cardiovascular outcome benefit has been a reduction in the risk of stroke, but reductions in myocardial infarction and cardiovascular mortality also have been seen regularly.

Elevated systolic or diastolic pressure causes increased cardiovascular risk, and the absolute risk increase per mmHg is greater at higher blood pressures, so that even modest reductions of severe hypertension can provide substantial benefit. Relative risk reduction from blood pressure reduction is similar across populations with varying absolute risk, so the absolute benefit is greater in patients who are at higher risk independent of their hypertension (for example, patients with diabetes or hyperlipidemia), and such patients would be expected to benefit from more aggressive treatment to a lower blood pressure goal.

Some antihypertensive drugs have smaller blood pressure effects (as monotherapy) in black patients, and many antihypertensive drugs have additional approved indications and effects (e.g., on angina, heart failure, or diabetic kidney disease). These considerations may guide selection of therapy.

Edarbi may be used alone or in combination with other antihypertensive agents.

CONTRAINDICATIONS None WARNINGS AND PRECAUTIONS Fetal/Neonatal Morbidity and Mortality Drugs that act directly on the renin-angiotensin system can cause fetal and neonatal morbidity and death when administered to pregnant women during the second and third trimester. When pregnancy is detected, Edarbi should be discontinued as soon as possible.

The use of drugs that act directly on the renin-angiotensin system during the second and third trimesters of pregnancy has been associated with fetal and neonatal injury, including hypotension, neonatal skull hypoplasia, anuria, reversible or irreversible renal failure, and death. Oligohydramnios has also been reported, presumably resulting from decreased fetal renal function; oligohydramnios in this setting has been associated with fetal limb contractures, craniofacial deformation, and hypoplastic lung development.

Prematurity, intrauterine growth retardation, and patent ductus arteriosus have also been reported, although it is not clear whether these occurrences were due to exposure to the drug.

These adverse effects do not appear to have resulted from intrauterine drug exposure that has been limited to the first trimester. Mothers whose embryos and fetuses are exposed to an angiotensin II receptor antagonist only during the first trimester should be so informed. Nonetheless, when patients become pregnant, physicians should have the patient discontinue the use of Edarbi as soon as possible.

Rarely (probably less often than once in every thousand pregnancies), no alternative to a drug acting on the renin-angiotensin system is available. In these rare cases, the mother should be apprised of the potential hazards to the fetus and serial ultrasound examinations should be performed to assess the intra-amniotic environment.

If oligohydramnios is observed, Edarbi should be discontinued unless it is considered life-saving for the mother. Contraction stress testing, a nonstress test or biophysical profiling may be appropriate, depending upon the week of pregnancy. Patients and physicians should be aware, however, that oligohydramnios may not appear until after the fetus has sustained irreversible injury.

Infants with histories of in utero exposure to an angiotensin II receptor antagonist should be closely observed for hypotension, oliguria, and hyperkalemia. If oliguria occurs, attention should be directed toward support of blood pressure and renal perfusion. Exchange transfusion or dialysis may be required as a means of reversing hypotension and/or substituting for impaired renal function.

Hypotension in Volume- or Salt-Depleted Patients In patients with an activated renin-angiotensin system, such as volume- and/or salt-depleted patients (eg, those being treated with high doses of diuretics), symptomatic hypotension may occur after initiation of treatment with Edarbi.

Correct volume or salt depletion prior to administration of Edarbi, or start treatment at 40 mg. If hypotension does occur, the patient should be placed in the supine position and, if necessary, given an intravenous infusion of normal saline. A transient hypotensive response is not a contraindication to further treatment, which usually can be continued without difficulty once the blood pressure has stabilized.

Impaired Renal Function As a consequence of inhibiting the renin-angiotensin system, changes in renal function may be anticipated in susceptible individuals treated with Edarbi.

In patients whose renal function may depend on the activity of the reninangiotensin system (e.g., patients with severe congestive heart failure, renal artery stenosis, or volume depletion), treatment with angiotensin-converting enzyme inhibitors and angiotensin receptor blockers has been associated with oliguria or progressive azotemia and rarely with acute renal failure and death.

Similar results may be anticipated in patients treated with Edarbi.

In studies of ACE inhibitors in patients with unilateral or bilateral renal artery stenosis, increases in serum creatinine or blood urea nitrogen have been reported. There has been no long-term use of Edarbi in patients with unilateral or bilateral renal artery stenosis, but similar results may be expected.

ADVERSE REACTIONS Clinical Trials Experience Because clinical trials are conducted under widely varying conditions, adverse reaction rates observed in the clinical trials of a drug cannot be directly compared to rates in the clinical trials of another drug and may not reflect the rates observed in practice.

A total of 4814 patients were evaluated for safety when treated with Edarbi at doses of 20, 40 or 80 mg in clinical trials. This includes 1704 patients treated for at least 6 months; of these, 588 were treated for at least 1 year.

Treatment with Edarbi was well-tolerated with an overall incidence of adverse reactions similar to placebo. The rate of withdrawals due to adverse events in placebo-controlled monotherapy and combination therapy trials was 2.4% (19/801) for placebo, 2.2% (24/1072) for Edarbi 40 mg, and 2.7% (29/1074) for Edarbi 80 mg. The most common adverse event leading to discontinuation, hypotension/orthostatic hypotension, was reported by 0.4% (8/2146) patients randomized to Edarbi 40 mg or 80 mg compared to 0% (0/801) patients randomized to placebo. Generally, adverse reactions were mild, not dose related and similar regardless of age, gender and race.

In placebo controlled monotherapy trials, diarrhea was reported up to 2% in patients treated with Edarbi 80 mg daily compared with 0.5% of patients on placebo.

Other adverse reactions with a plausible relationship to treatment that have been reported with an incidence of â&#x2030;Ľ0.3% and greater than placebo in more than 3300 patients treated with Edarbi in controlled trials are listed below: Gastrointestinal Disorders: nausea General Disorders and Administration Site Conditions: asthenia, fatigue Musculoskeletal and Connective Tissue Disorders: muscle spasm Nervous System Disorders: dizziness, dizziness postural Respiratory, Thoracic and Mediastinal Disorders: cough Clinical Laboratory Findings In controlled clinical trials, clinically relevant changes in standard laboratory parameters were uncommon with administration of Edarbi.

Serum creatinine: Small reversible increases in serum creatinine are seen in patients receiving 80 mg of Edarbi. The increase may be larger when coadministered with chlorthalidone or hydrochlorothiazide.

In addition, patients taking Edarbi who had moderate to severe renal impairment at baseline or who were >75 years of age were more likely to report serum creatinine increases.

Hemoglobin/Hematocrit: Low hemoglobin, hematocrit, and RBC counts were observed in 0.2%, 0.4%, and 0.3% of Edarbi-treated subjects, respectively.

None of these abnormalities were reported in the placebo group. Low and high markedly abnormal platelet and WBC counts were observed in <0.1% of subjects.

DRUG INTERACTIONS No clinically significant drug interactions have been observed in studies of azilsartan medoxomil or azilsartan given with amlodipine, antacids, chlorthalidone, digoxin, fluconazole, glyburide, ketoconazole, metformin, pioglitazone, and warfarin. Therefore, Edarbi may be used concomitantly with these medications.

Non-Steroidal Anti-Inflammatory Agents including Selective Cyclooxygenase-2 Inhibitors (COX-2 Inhibitors) In patients who are elderly, volume-depleted (including those on diuretic therapy), or who have compromised renal function, co-administration of NSAIDs, including selective COX-2 inhibitors, with angiotensin II receptor antagonists, including azilsartan, may result in deterioration of renal function, including possible acute renal failure. These effects are usually reversible. Monitor renal function periodically in patients receiving azilsartan and NSAID therapy.

The antihypertensive effect of angiotensin II receptor antagonists, including azilsartan, may be attenuated by NSAIDs, including selective COX-2 inhibitors.

USE IN SPECIFIC POPULATIONS Pregnancy Pregnancy Category C (first trimester) and D (second and third trimesters).

There is no clinical experience with the use of Edarbi in pregnant women.

Nursing Mothers It is not known if azilsartan is excreted in human milk, but azilsartan is excreted at low concentrations in the milk of lactating rats. Because of the potential for adverse effects on the nursing infant, a decision should be made whether to discontinue nursing or discontinue the drug, taking into account the importance of the drug to the mother.

Pediatric Use Safety and effectiveness in pediatric patients under 18 years of age have not been established.

Geriatric Use No dose adjustment with Edarbi is necessary in elderly patients. Of the total patients in clinical studies with Edarbi, 26% were elderly (65 years of age and older); 5% were 75 years of age and older. Abnormally high serum creatinine values were more likely to be reported for patients age 75 or older. No other differences in safety or effectiveness were observed between elderly patients and younger patients, but greater sensitivity of some older individuals cannot be ruled out.

Renal Impairment Dose adjustment is not required in patients with mild-to-severe renal impairment or end-stage renal disease. Patients with moderate to severe renal impairment are more likely to report abnormally high serum creatinine values.

Hepatic Impairment No dose adjustment is necessary for subjects with mild or moderate hepatic impairment. Edarbi has not been studied in patients with severe hepatic impairment.

OVERDOSAGE Limited data are available related to overdosage in humans. During controlled clinical trials in healthy subjects, once daily doses up to 320 mg of Edarbi were administered for 7 days and were well tolerated. In the event of an overdose, supportive therapy should be instituted as dictated by the patientâ&#x20AC;&#x2122;s clinical status. Azilsartan is not dialyzable.

CLINICAL PHARMACOLOGY Pharmacokinetics Special Populations The effect of demographic and functional factors on the pharmacokinetics of azilsartan was studied in single and multiple dose studies. Pharmacokinetic measures indicating the magnitude of the effect on azilsartan are presented in Figure 1 as change relative to reference (test/reference). Effects are modest and do not call for dosage adjustment.

Figure 1 Impact of intrinsic factors on the pharmacokinetics of azilsartan Population Description

PK

Fold Change and 90% CI

Recommendation

AGE

Cmax AUC

No dose adjustment

Cmax AUC

No dose adjustment

Cmax AUC

No dose adjustment

Mild/Normal

Cmax AUC

No dose adjustment

Moderate/Normal

Cmax AUC

No dose adjustment

Severe/Normal

Cmax AUC

No dose adjustment

ESRD/Normal

Cmax AUC

No dose adjustment

Mild/Normal

Cmax AUC

No dose adjustment

Moderate/Normal

Cmax AUC

No dose adjustment

>65y/18-45y GENDER Females/Males RACE Whites/Blacks RENAL IMPAIRMENT

HEPATIC IMPAIRMENT

Severe/Normal

NO EXPERIENCE NO EXPERIENCE

PEDIATRIC

0.5

1.0

1.5

2.0

Change relative to reference

2.5

3.0

NONCLINICAL TOXICOLOGY Carcinogenesis, Mutagenesis, Impairment of Fertility Carcinogenesis: Azilsartan medoxomil was not carcinogenic when assessed in 26-week transgenic (Tg.rasH2) mouse and 2-year rat studies. The highest doses tested (450 mg azilsartan medoxomil/kg/day in the mouse and 600 mg azilsartan medoxomil/kg/day in the rat) produced exposures to azilsartan that are 12 (mice) and 27 (rats) times the average exposure to azilsartan in humans given the maximum recommended human dose (MRHD, 80 mg azilsartan medoxomil/day). M-II was not carcinogenic when assessed in 26-week Tg.rasH2 mouse and 2-year rat studies. The highest doses tested (approximately 8000 mg M-II/kg/day (males) and 11,000 mg M-II/kg/day (females) in the mouse and 1000 mg M-II/kg/day (males) and up to 3000 mg M-II/kg/day (females) in the rat) produced exposures that are, on average, about 30 (mice) and 7 (rats) times the average exposure to M-II in humans at the MRHD. Mutagenesis: Azilsartan medoxomil, azilsartan, and M-II were positive for structural aberrations in the Chinese Hamster Lung Cytogenetic Assay. In this assay, structural chromosomal aberrations were observed with the prodrug, azilsartan medoxomil, without metabolic activation. The active moiety, azilsartan was also positive in this assay both with and without metabolic activation. The major human metabolite, M-II was also positive in this assay during a 24 hr assay without metabolic activation.

Azilsartan medoxomil, azilsartan, and M-II were devoid of genotoxic potential in the Ames reverse mutation assay with Salmonella typhimurium and Escherichia coli, the in vitro Chinese Hamster Ovary Cell forward mutation assay, the in vitro mouse lymphoma (tk) gene mutation test, the ex vivo unscheduled DNA synthesis test, and the in vivo mouse and/or rat bone marrow micronucleus assay.

Impairment of Fertility: There was no effect of azilsartan medoxomil on the fertility of male or female rats at oral doses of up to 1000 mg azilsartan medoxomil/kg/day [6000 mg/m2 (approximately 122 times the MRHD of 80 mg azilsartan medoxomil/60 kg on a mg/m2 basis)]. Fertility of rats also was unaffected at doses of up to 3000 mg M-II/kg/day.

PATIENT COUNSELING INFORMATION See FDA-approved patient labeling (Patient Information).

General Information Pregnancy: Female patients of childbearing age should be told that use of drugs like Edarbi that act on the renin-angiotensin system during pregnancy can cause serious problems in the fetus and infant including low blood pressure, poor development of skull bones, kidney failure, and death. These consequences do not appear to have resulted from intrauterine drug exposure that has been limited to the first trimester. Discuss other treatment options with female patients planning to become pregnant. Women using Edarbi who become pregnant should notify their physicians as soon as possible.

Distributed by Takeda Pharmaceuticals America, Inc. Deerfield, IL 60015 For more detailed information, see the full prescribing information for Edarbi at www.edarbi.com or contact Takeda Pharmaceuticals America, Inc. at 1-877-825-3327.

Edarbi is a trademark of Takeda Pharmaceutical Company Limited registered with the U.S. Patent and Trademark Office and used under license by Takeda Pharmaceuticals America, Inc. Š2011 Takeda Pharmaceuticals America, Inc. April 2011 AZL074 R2 L-LXA-0411-4

SEPTEMBER 2011

VOLUME 4, NUMBER 5

THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™

™

™

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

TABLE OF CONTENTS

(Continued)

CLINICAL

303 Current Therapies and Emerging Drugs in the Pipeline for Type 2 Diabetes Quang T. Nguyen, DO; Karmella T. Thomas, BS, RD; Katie B. Lyons, MS II; Loida D. Nguyen, PharmD, BCBS; Raymond A. Plodkowski, MD 311 Stakeholder Perspective by James V. Felicetta, MD

312 Lipid Management in Patients with Type 2 Diabetes Marsha J. Daniel, PharmD, cPh, CDE 321 Stakeholder Perspective by Gary M. Owens, MD

American Health & Drug Benefits, ISSN 1942-2962 (print); ISSN 1942-2970 (online), is published 6 times a year by Engage Healthcare Communications, LLC, 241 Forsgate Drive, Suite 205A, Monroe Township, NJ 08831. Copyright © 2011 by Engage Healthcare Communications, LLC. All rights reserved. American Health & Drug Benefits and The Peer-Reviewed Forum for Evidence in Benefit Design are trademarks of Engage Healthcare Communications, LLC. No part of this publication may be reproduced or transmitted in any form or by any means now or hereafter known, electronic or mechanical, including photocopy, recording, or any informational storage and retrieval system, without written permission from the Publisher.

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www.tradjenta.com Copyright Š2011, Boehringer Ingelheim Pharmaceuticals, Inc. All rights reserved. (5/11) TJ94982MHC

INTRODUCTION

In Search of Stakeholder Collaboration to Stem the Cardiometabolic Epidemic Dalia Buffery, MA, ABD

T

he numbers are staggering. According to the American Heart Association, 76.4 million Americans have hypertension, 16.3 million have chronic heart disease, 5.7 million have heart failure, and 7 million have stroke.1 Data from the Centers for Disease Control and Prevention show that 25.8 million Americans had diabetes and many millions more had prediabetes in 2007.2 The link between cardiovascular disease (CVD) and diabetes is well known,2 and the numbers of overweight and obese Americans continue to climb, further fueling the prevalence of cardiometabolic risk factors that can be categorized under the umbrella of a newly defined cardiometabolic disease.

Cardiometabolic disease consists of a constellation of risk factors associated with CVD and metabolic syndrome that include dyslipidemia, hypertension, insulin resistance, and high abdominal fat. In practical terms, it is impossible to separate the risk assessment and management of CVD and metabolic syndrome.

Despite the many advances in CVD interventions, heart disease continues to be the number one killer of Americans.3 And even with the availability of many antihyperglycemic drug classes, less than half of diabetic patients reach the American Diabetes Association’s glycemic goal of hemoglobin A1c <7%.4 Add to this the astronomical costs utilized independently to manage CVD, dyslipidemia, diabetes (and its complications), and obesity, and the picture becomes truly gloomy: In 2007, the estimated total US costs for diabetes were $174 billion.2 In 2008, the estimated total costs for obesity were $147 billion. In 2010, the direct costs for CVD were $272.5 billion, and these are expected to reach $818.1 billion in 20305—at a time when the US economic outlook is not too promising.

It may indeed take a crisis of illness and economics of this magnitude to get providers, payers, manufacturers, patients (especially patients), and policymakers to collaborate on a mutual goal of changing people’s attitudes toward health and disease and helping to transform our healthcare system from one that spends billions of dollars on postdisease interventions to one that embraces predisease prevention efforts as key to cardiometabolic health. To make a real difference in this growing epidemic that is in part dependent on lifestyle and personal choices, it is necessary to fully engage individuals in their own cardiometabolic wellness, in addition to any

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pharmacotherapeutic interventions, as the authors in this issue make clear.

This theme issue of American Health & Drug Benefits is a step toward raising awareness of the cardiometabolic constellation of risk factors and the urgent need for collaboration among stakeholders. Colombi and Wood present their study’s results on the impact of obesity on care utilization and cost of cardiovascular conditions for a large employer, demonstrating that worksites with the highest rates of obesity had significantly more episodes of care (of any type) than sites with leaner workers. In their call to action, Page and colleagues sound the alarm about the growing risk for CVD among American young adults, focusing on the need to develop prevention strategies for this population and not only for older adults. Nguyen and colleagues outline the many drug therapies available for diabetes and discuss the new drugs in development, many of which have new mechanisms of action and fewer side effects, such as weight gain.

Riordan and colleagues highlight the association between CVD and schizophrenia, noting that CVD is the most common cause of natural mortality in schizophrenia, with increased prevalence of dyslipidemia, hypertension, obesity, and diabetes in this patient population.6 Finally, Daniel provides a comprehensive review of current lipid goals in diabetic patients, outlining the appropriate use of available pharmacotherapies when lifestyle changes fail.

A single issue cannot cover the full scope of cardiometabolic risk factors and potential solutions.

Readers are invited to submit articles to the journal that begin to chart novel ways of transitioning the US healthcare system into a new era of cardiometabolic health and wellness. ■

References 1. Roger VL, Go AS, Lloyd-Jones DM, et al, for the American Heart Association.

Heart disease and stroke statistics—2011 update. Circulation. 2011;123:e18-e209.

2. Centers for Disease Control and Prevention. 2011 National diabetes fact sheet. www.cdc.gov/diabetes/pubs/estimates11.htm#11. Accessed September 23, 2011.

3. Kochanek K, Xu J, Murphy SL, et al. Deaths: preliminary data for 2009. Natl Vital Stat Rep. 2011;59:1-51.

4. Fitch K, Iwasaki K, Pyenson B. Improved management can help reduce the economic burden of type 2 diabetes: a 20-year actuarial projection. Milliman Client Report.

April 28, 2010. http://publications.milliman.com/publications/health-published/ pdfs/improved-management-can-help.pdf. Accessed September 7, 2011.

5. Heidenreich PA, Trogdon JG, Khavjou OA, et al, for the American Heart Association. Forecasting the future of cardiovascular disease in the United States.

Circulation. 2011;123:933-944.

6. Newcomer JW. Second-generation (atypical) antipsychotics and metabolic effects: a comprehensive literature review. CNS Drugs. 2005;19(suppl 1):1-93.

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ORIGINAL RESEARCH

Obesity in the Workplace: Impact on Cardiovascular Disease, Cost, and Utilization of Care Alberto M. Colombi, MD, MPH; G. Craig Wood, MS Background: In forecasting the future of cardiovascular disease (CVD), the American Heart Association calls for preventive strategies with particular attention to obesity. The association between obesity and CVD, including coronary artery disease (CAD) and diabetes, is well established. The rising prevalence of obesity in the workforce may have additional implications for employers and employees besides the demonstrated effects on absenteeism and workersâ&#x20AC;&#x2122; compensation.

Objective: This study was undertaken to determine the impact of population obesity on care utilization and cost of cardiovascular conditions such as hypertension, CAD, and cerebrovascular disease (or stroke) in a large US population of employees engaged in a major corporate wellness program.

Study sample: Using data from a single large industrial employer across 29 geographically distinct worksites in the United States, 179,708 episodes of care from 2004 to 2007 for 10,853 employees were included.

Methods: The population-based economic impact of obesity was calculated on the basis of the frequency of episodes of care per 1000 employees and on the amount eligible for payment per episode of care in US dollars. Data were obtained from a wellness program databases, episode of illness inventories, and pharmacy and medical claims. High and low prevalence rates of obesity, by obesity quartile, were used to create linear mixed models to examine associations with disease outcomes, while controlling for correlation within each worksite.

Results: Worksites with a high rate of obesity (ie, in the fourth quartile) had 348.4 more episodes of care of any kind per 1000 employees (P <.001), 38.6 more hypertension episodes of care per 1000 employees (P <.001), and 2.5 more cerebrovascular disease episodes of care per 1000 employees (P = .017) compared with worksites in the lower 3 quartiles. A worksite in the fourth obesity rate quartile had $223 greater cost per any kind of episode (P <.001), $169 greater cost per hypertension episode (P = .003), and $1620 more per CAD episode (P = .005) compared with worksites in the lower 3 quartiles. The overall economic impact per 1000 employees was calculated by combining episode frequency and eligible amount for payment per episode. For sites in the lower 3 quartiles of obesity, the eligible amount per 1000 employees for any kind of care was $4.01 million. However, for sites in the highest obesity quartile, the eligible amount for payment per 1000 employees was $5.26 million. This translates into $1250 greater cost per employee. Similar calculations were used to evaluate the effect of obesity on the amount eligible for payment per employee for hypertension, CAD, and cerebrovascular disease episodes, with an estimated $69, $89, and $8 greater cost, respectively, per employee.

Conclusion: Worksites with greater obesity prevalence rates were associated with numerically more frequent and more expensive episodes of care than worksites with low obesity prevalence.

I

n forecasting the future of cardiovascular disease (CVD), the American Heart Association calls for preventive strategies, with particular attention to

Dr Colombi is Corporate Medical Director, PPG Industries, Pittsburgh, PA; Mr Wood is a Senior Biostatistician, Center for Health Research, Geisinger Clinic, Danville, PA.

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Alberto Colombi

Stakeholder Perspective, page 278

Am Health Drug Benefits.

2011;4(5):271-278 www.AHDBonline.com Disclosures are at end of text

obesity.1 The facts related to the current obesity epidemic are familiar, stark, and bode bad news not only for the physical health of the US population but also for its economic health. Obesity is a common denominator in and a risk factor for many chronic conditions, including diabetes, coronary artery disease (CAD), stroke, and hypertension.2,3

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KEY POINTS ➤

➤

➤

➤

➤

➤

According to the Centers for Disease Control and Prevention, the medical costs for obese persons are $1429 higher than for normal-weight individuals.

The American Heart Association has called for implementing prevention strategies, with particular attention to obesity, to reduce the burden of heart disease.

This study examined the impact of obesity on care utilization and cost in a large population of employees enrolled at a wellness program in 29 worksites at PPG Industries.

Results showed that the mean number of episodes of care per 1000 employees was higher in sites with the highest rates of obesity compared with sites with lower rates of obesity, including episodes of care for coronary artery disease, stroke, and hypertension.

The wellness program enrollees who were more obese had 348.4 more episodes of care per 1000 employees annually, with a total annual cost of $1250 per patient.

These results demonstrate that worksites with higher proportions of obese employees have higher utilization rates and higher costs of care, which are of particular concern for financially marginal or stressed employers, and for the self-insured employers who cover the healthcare costs of their employees.

In 2008, the annual direct and indirect costs of obesity were estimated to be $147 billion.4 Recent estimates of the financial cost of obesity range from a few hundred dollars for the mildly overweight male to almost $7000 for the female with a body mass index (BMI) >40 kg/m2 (ie, grade 3).5 The Centers for Disease Control and Prevention has proposed that “persons who are obese have medical costs that are $1429 higher than those of normal weight.”6 The contributions to this cost include increased workers’ compensation,7 absenteeism,8 presenteeism (ie, being at work but underproductive), direct medical costs, and costs attributable to the contribution of obesity to the development and exacerbation of a chronic condition.9 The longitudinal trend is such that the prevalence of obesity in adults in the United States has doubled between 1984 and 2004.10 The recent National Health and Nutrition Examination Survey analysis showed that the prevalence of obesity in almost every age-group and in both sexes exceeded 30%.11 In light of these daunting epidemiologic and fiscal trends, there is intense focus in the political and the research spheres to “bend the cost curve” down. Several

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approaches have been proposed, including some that are multifactorial, addressing patient needs beyond the clinical encounter. One multifactorial approach is the chronic care model developed by Wagner and colleagues that is intended to improve outcomes by changing chronic disease care from an acute and reactive model to a proactive, planned, and population-based model that incorporates community resources, information technology, and self-management support in care.12,13 Wellness programs also comprise a multifactorial approach to health improvement and health promotion, including the management of chronic conditions.14 Unlike care models with a more macro, system-level focus, wellness programs have been studied extensively over the past 30 years.

A recent review showed strong evidence linking wellness programs to improvements in tobacco use, alcohol use, nonuse of seatbelts, dietary fat intake, blood pressure, absenteeism, and healthcare service use.15 Such programs characteristically focus on understanding patientlevel risk and in supporting patients in achieving beneficial, proximal outcomes, such as smoking cessation, weight reduction, and reduced alcohol intake.

Wellness programs have been developed by employers to reach potential or actual patients where they work, and address employee health, absenteeism, presenteeism, and escalating costs.

This study was undertaken to determine the impact of population obesity on care utilization and cost of certain cardiovascular conditions in a large population of employees engaged in a major corporate wellness program.

Methods PPG Industries—a global supplier of coatings, optical products, specialty materials, chemicals, glass, and fiberglass—is headquartered in Pittsburgh, PA, had more than 30 US manufacturing sites and about 15,000 employees at the time of this study. In the context of a company wellness program described elsewhere,16 the incremental effect of worksite population obesity prevalence on care utilization and cost of certain CVD conditions (ie, hypertension, CAD, and cerebrovascular disease [or stroke]) at several worksites was assessed.

Claims provided by group health insurance contracts where the employer is self-insured were trusted to be complete, whereas claims derived from fully insured health maintenance organizations were considered to be incomplete. The only worksites included in this study were those that as of December 31, 2007, were self-insured, had at least 50 employees, and at least 70% of their employees had taken the online health risk appraisal at least once. The health risk of the population was based on the responses of those who took

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the health risk appraisal at least once. The claims were all the claims available for each worksite.

Data from 29 such worksites—including active, fulltime PPG employees aged 35 to 74 years during 20042007—were then analyzed as to care claims utilization and cost. Employees in each worksite were exposed to PPG’s Wellness Program Inventory, a wellness program modeled after the “10 Keys to Healthy Aging” program developed at the University of Pittsburgh.17

Data Collection, Outcome Measures An online health risk appraisal provided through Infotech’s Wellness Checkpoint was available to all employees during the study period.18 Wellness Checkpoint also provided comprehensive data on employee health and risks relevant to population level health and wellness measurement tracking and management.

Worksite (health risk appraisal) responses—designed to provide employees with individualized information on health risks and health priorities—completed by employees online from 2004 to 2007 were aggregated to create population rates and indicators of risk. Medical and pharmaceutical claims data for PPG employees were obtained from Thomson Reuters Advantage Suite database, a commercially available database.19 Healthcare utilization data were collected for employees who had at least 320 days of healthcare coverage benefits during each of the study years of interest. Each patient’s data were limited to episodes of care that occurred while the individual was employed at 1 of the 29 PPG worksites during the study period. The data were available at each worksite and were stratified by sex, age, and year.

Within each stratum, healthcare utilization measures were grouped into episodes of care using Thomson Reuters Medical Episode Grouper software,20 which combines all inpatient, outpatient, and/or prescription treatments related to a single discrete occurrence of illness. During the study period, all distinct episodes of care of any type and episodes of care for 3 specific conditions—CAD, cerebrovascular disease, and hypertension—were identified.

Utilization and cost of care were the primary outcome measures. For each of 4 categories of episode grouping (overall, CAD, cerebrovascular disease, and hypertension), 4 metrics were summarized, including the total number of episodes of care, the number of episodes per 1000 active employees, the total amount eligible for payment per episode, and the total amount eligible for payment per 1000 employees.

Definitions “Utilization” was defined as the number of episodes of

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care per 1000 active employees. This measure was created by calculating the average number of episodes of care per 1000 members who had medical insurance coverage during the year.

“Episodes of care” was defined as a summary of inpatient, outpatient, and prescription treatment related to a given illness episode associated with the underlying details occurring within a defined time window.

“Episodes per 1000” was defined as the average number of episodes of care per 1000 active employees who had medical coverage annually ([episodes/(employees’ months of medical coverage/1000)] × 12).

“Cost” was defined as the total allowed amount that was eligible for payment per episode of care. This was therefore defined as the total amount of submitted charges eligible for payment for facility, medical, and prescriptions included in the episodes of care. It is the amount eligible after applying pricing guidelines but before deducting third-party, copayment, coinsurance, or deductible amounts. As such, it measured the total eligible cost of an episode of care. Although “eligible amount” is not always the actual paid amount—which is a function of health insurance negotiations with care providers—it provides a comparable common denominator across different group health plans servicing various worksites.

The primary independent variable for this study was obesity prevalence status at each worksite. Because the obesity status of individual claims was not available, obesity status was estimated by aggregating the health risk appraisal responses of percent health risk appraisal users at each worksite. Only worksites with at least a 70% health risk appraisal completion rate were included.

Within each worksite, the percent of employees who were obese (BMI >30 kg/m2) based on their aggregate responses was calculated. We then stratified each worksite’s obesity prevalence into quartiles, based on the percent of obesity reported at each site. These percentages were used to categorize the worksites into quartiles, based on highest (and lowest) percent obese. For analytic purposes, worksites in the fourth quartile were classified as a high-rate obesity.

Other independent variables in the analysis included sex (male or female), age (5-year increments from 35-49 to 50-64 and 65-74), year (2004, 2005, 2006, 2007), and total number of episodes (a surrogate measure for size of a given site).

Statistical analyses were conducted using SAS version 9.2 (Cary, NC). The analyses aimed to determine if worksite obesity status was associated with increased frequency of episodes of care and higher costs for all episodes, and then, separately, for hypertension, CAD, and cerebrovascular disease episodes of care. Linear

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Unadjusted Mean Episodes per 1000 Active Employees and Mean Cost Amount Eligible for Payment Table 1 per Episode, by Obesity Status and Episode Type Episode type

A. Mean number of episodes per 1000 active employees, N B. Mean allowed payment per episode, $ C. Economic impact per 1000 active employees (A Ă&#x2014; B), $

Any

Hypertension

CAD

Cerebrovascular disease

Obese sitea

3795

201

42

13

Nonobese site

3388

156

33

7

Obese sitea

1418

1098

7418

2919

Nonobese site

1186

929

5674

2599

Obese sitea

5,381,310

220,698

311,556

37,947

Nonobese site

4,018,168

144,924

187,242

18,193

Ratio

1.33

1.52

1.66

2.09

a

Obese sites were defined as the 8 sites with the highest obesity rates (ie, fourth quartile of obesity).

CAD indicates coronary artery disease.

mixed models were used to examine associations while controlling for correlations within a given worksite.

This model was chosen to preserve the overall sample size of 29 worksites while controlling for the effects of

The mean number of episodes per 1000 employees was higher in sites with the highest rates of obesity compared with sites in the lower 3 quartiles of obesity. This relationship was consistent for all episode types and for episodes of hypertension, CAD, and cerebrovascular disease. site size, sex, age, and year of observation. In sensitivity analysis, 1 possible outlier was identified; however, this did not have an influence on the results. The same results were observed whether the outlier was included or not. As a result, we conducted the analysis without removing the outlier. All tests were 2-sided, and P <.05 was considered significant.

Results A total of 179,708 episodes of care across 29 worksites were examined. Across the entire study population, the average number of episodes per 1000 employees was 3504, and the average allowed amount per episode was $1252. Of these episodes, 8493 (4.7%) were for hypertension, 1611 (0.9%) were defined as CAD, and 467 (0.3%) were defined as cerebrovascular disease (stroke) episodes

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(and 5.9% related to the 3 subgroups examined further).

From 2004 to 2007, 10,853 employees participated in the health risk appraisal while employed at 1 of the 29 PPG worksites that met the inclusion criteria. Across all worksites, 71% of the employees were men. The percentages of employees by age-groups included 13% aged 35 to 39 years; 17% aged 40 to 44 years; 23% aged 45 to 49 years; 24% aged 50 to 54 years; 17% aged 55 to 59 years; and 6% aged â&#x2030;Ľ60 years.

The number of employee participants in each of the 29 sites (range of employees per site, 50-3568) included 2 sites with <100 participants, 12 sites with 100 to 999 participants, and 15 sites with >1000 employee participants. Men had considerably fewer episodes of care per 1000 than women; younger employees had fewer episodes of care than older employees.

The (unadjusted) mean number of episodes per 1000 employees was higher in sites with the highest rates of obesity (ie, sites in the fourth obesity quartile) compared with sites in the lower 3 quartiles of obesity. This relationship was consistent for all episode types and for episodes of hypertension, CAD, and cerebrovascular disease (Table 1). A similar pattern was observed when comparing the unadjusted average allowed amount eligible for payment per episode between sites with high rates of obesity and sites in the lower 3 quartiles for obesity rates.

To determine if the differences between sites with high rates of obesity and other sites persisted after controlling for the number of episodes, calendar year of observation, age, and sex, additional analyses were completed. Controlling for year was included to account for

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changes in cost over time (ie, to help offset the opposing forces of inflation and increases in efficient healthcare).

Worksites with a high rate of obesity (ie, in the fourth quartile) had 348.4 more episodes of care per 1000 employees (P <.001), 38.6 more hypertension episodes of care per 1000 employees (P <.001), and 2.5 more cerebrovascular episodes of care per 1000 employees (P = .017) compared with a worksite in the lower 3 quartiles (Table 2). Total number of episodes, age, sex, and year were also significantly related to number of episodes per 1000 employees.

A worksite with a high rate of obesity (ie, in the fourth quartile) had $223.2 greater cost per any episode (P <.001), $169 greater cost per hypertension episode (P = .003), and $1620 greater cost per CAD episode (P = .005) compared with worksites in the lower 3 quartiles (Table 3). Similarly, the total number of episodes, age, sex, and year were significantly related to the cost per episode of care.

To evaluate the overall economic impact of obesity per 1000 employees, the episode rate was multiplied by

the corresponding amount eligible for payment per episode. For sites in the lower 3 quartiles of obesity, the eligible amount per 1000 employees was $4.01 million (mean episodes per 1000 employees [3388] × allowed amount per episode [$1186]).

However, for sites in the highest obesity quartile, the eligible amount per 1000 employees was $5.26 million (mean episodes per 1000 employees [3388 + 348] × allowed amount per episode [$1186 + $223]). This difference translates into $1250 more per employee.

Similar calculations were used to evaluate the effect of obesity on eligible payment amount per employee for hypertension, CAD, and cerebrovascular disease episodes, with an estimated $69, $89, and $8 greater cost per employee, respectively.

The overall economic impact was 1.33 higher for any episode, 1.52 higher for hypertension episodes, 1.66 higher for CAD episodes, and 2.09 higher for cerebrovascular disease episodes in worksites having the highest rates of obesity (ie, sites in the fourth quartile for obesity) compared with sites in the lower 3 quartiles of obesity.

Table 2 Association of Episodes per 1000 Employees with Each Independent Variable, by Episode Type Any episode Variable

Hypertension

Estimate, N P value Estimate, N P value Estimate, N P value Estimate, N P value 5497.1

Intercept

Cerebrovascular disease

CAD

356.9

117.0

9.6

1.0

.59

23.5

<.001a

107.8

<.001a

172.3

<.001a

Year 2004

–147.6

.070

–78.6

<.001a

–6.9

.16

2.0

.13

Year 2005

–24.2

.76

–6.3

.57

–1.6

.74

–0.3

.78

Year 2006

49.1

.53

–7.1

.52

5.1

.28

–0.5

.69

Year 2007

Reference

Increase of 10 episodes

1474.6

Women Men

Reference a

<.001

Reference

–21.8

Reference a

–15.2

.010

Reference

–0.5

.002

Reference

Reference

–3127.9

<.001

–208.2

<.001

–100.2

<.001

–6.9

.002a

Age 50-64 yrs

–2225.7

<.001a

–101.4

<.001a

–77.6

<.001a

–4.6

.010a

Age 65-74 yrs

Reference 348.4

Lowest quartiles of obesity (Q1-Q3)

Reference

a

.56

Age 35-49 yrs

Highest quartile of obesity (Q4)

a

Reference a

Reference <.001a

38.6

Reference

Reference .001a

4.9

Reference .20

Reference

a

2.5

.017a

Reference

NOTE: Estimates are in number of episodes. a Significant difference, P <.05.

CAD indicates coronary artery disease.

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Discussion Among patients exposed to a workplace wellness management program, we found that higher obesity rates are associated with more frequent and more expensive episodes of care. In this study, worksite obesity prevalence is associated with a significantly higher occurrence of episodes of care of all types, including those for hypertension, CAD, and stroke.

Obesity prevalence is associated with a significant increase in costs per episode for hypertension and CAD, but the cost is not significantly greater for stroke.

These results confirm the general conclusions in the literature that obesity increases care incidence, prevalence, and the cost of cerebrovascular disease,1-4 and that it is therefore a worthy focus for cost reduction through management. That these findings were not obtained through a disease filter but from wellness program enrollees—as described elsewhere16—suggests that a workplace focus on obesity prevention may prove useful in designing programs meant to lower costs and morbidities.

As our results demonstrate, worksites with higher pro-

portions of obese employees have higher utilization rates and higher costs of care. Such costs are of particular concern for financially marginal or stressed employers and for the self-insured employers who ultimately cover the healthcare costs of their employees. The impact on non– self-insured employers is also significant, because they must either absorb—or require employees to absorb via increased premiums—the costs associated with insuring companies with higher rates of obesity.

In this study we did not directly evaluate the impact of the wellness program itself. There is clearly an opportunity to make marked gains in health and healthcare utilization at such sites, because workplace wellness programs have demonstrated improvements in outcomes.21 There is also evidence that the management modalities (the “how”) of worksite wellness implementation are as important as the type of wellness programs (the “what”) offered in ultimately mitigating chronic disease– related healthcare costs.16 In this prospective population, health management acquires a renewed interest.

Effective management of chronic diseases and related

Table 3 Association of Cost Amount Eligible for Payment per Episode of Care and Each Independent Variable,

by Episode Type Any episode Variable Intercept

Hypertension

Cerebrovascular disease

CAD

Estimate, $ P value Estimate, $ P value Estimate, $ P value Estimate, $ P value 2128.1

1284.2

4626

320

1.3

.36

32.5

.23

2743

.005a

2479

.197

Year 2004

–314.9

<.001a

–294.9

.001a

1989

.017a

773

.19

Year 2005

–172.1

.009a

136.0

.036a

563

.40

524

.19

Year 2006

–80.8

.22

32.4

.61

1167

.080

462

.39

Year 2007

Reference

Increase of 10 episodes

Female Male

Reference <.001a

–237.3

Reference

16.1

Reference .74

Reference

–919

Reference .094

Reference

197

.62

Reference

Age 35-49 yrs

–668.0

<.001a

–371.0

.001a

1772

.094

1587

.085

Age 50-64 yrs

–365.0

<.001a

–115.9

.26

1608

.12

1889

.037a

Age 65-74 yrs

Reference

Reference <.001a

Highest quartile of obesity (Q4)

223.2

Lowest quartiles of obesity (Q1-Q3)

Reference

169.0

Reference

Reference .003a

1620

Reference

Reference .005a

206

.62

Reference

a

Significant difference, P <.05.

CAD indicates coronary artery disease.

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risk factors, such as obesity (much of which depends on health behavior change), is a complex task for patients and for their caregivers. Further research is needed to understand how to effect the necessary behavior change and which changes are best addressed in a clinical versus a workplace environment.

Limitations In this study we did not assess the role of the surrounding communities, particularly in regard to the availability of primary care, which is important for the detection, management, and intensity of episodic treatment and cost.

We used population-level data rather than individual-level data to characterize the relationship between obesity and utilization and obesity and costs. The results of our ecologic analysis, therefore, may not reflect individual-level relationships.

Our assessment of the rate of obesity within specific worksites is based on health risk appraisal data. We required 70% health risk appraisal participation at included worksites. We do not know whether health risk appraisal respondents differ from nonresponders in meaningful ways (eg, BMI).

In addition, we cannot determine the directionality of the association between obesity and utilization and costs, although worksites striving to reduce their population obesity rate may be encouraged by the association.

Finally, our data reflect one employer in a particular industry, and our results, therefore, may not extend to other employers in the same industry or to employees in different industries, although the “business case” for worksite obesity wellness programs is reinforced.

Conclusion Workplace wellness program enrollees in a single large manufacturing company who are more obese experience 348.4 more episodes of care per 1000 employees annually, which are also more expensive, with an annual total of $1250 per patient. These relationships hold true for all episodes of care and in particular for episodes involving hypertension, CAD, and cerebrovascular disease. Such costs are of particular concern for financially stressed employers, and for self-insured employers who cover the healthcare costs of their employees. Efforts aimed at controlling costs of healthcare might appropriately regard obesity as a marker for higher costs and episodes of care and design nutrition, physical activity, and weight management programs to reduce these clinical outcomes.

Acknowledgments Data extraction and statistical processing costs were supported by an unrestricted research grant from AstraZeneca, which had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. We thank Nirav R. Shah, MD, for providing insight to this effort and to the integrity of the data and the accuracy of the data analysis.

Author Disclosure Statement Dr Colombi and Mr Wood reported no conflicts of interest.

References 1. Heidenreich PA, Trogdon JG, Khavjou OA, et al. Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation. 2011;123:933-944.

2. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 2006;295:1549-1555.

3. National Center for Chronic Disease Prevention and Health Promotion. Chronic diseases: the power to prevent, the call to control. 2009. www.cdc.gov/chronicdisease/ resources/publications/AAG/pdf/chronic.pdf. Accessed October 1, 2010.

4. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. Annual medical spending attributable to obesity: payer- and service-specific estimates. Health Aff (Millwood).

2009;28:w822-w831.

5. Finklestein EA, DiBonaventura M, Burgess SM, Hale BC. The costs of obesity in the workplace. J Occup Environ Med. 2010;52:971-976.

6. Centers for Disease Control and Prevention-CDC Vital Signs-Adult Obesity.

August 3, 2010. www.cdc.gov/VitalSigns/pdf/2010-08-vitalsigns.pdf. Accessed August 26, 2011.

7. Ostbye T, Dement JM, Krause KM. Obesity and workers’ compensation: results from the Duke Health and Safety Surveillance System. Arch Intern Med. 2007;167: 766-773.

8. Cawley J, Rizzo JA, Haas K. Occupation-specific absenteeism costs associated with obesity and morbid obesity. J Occup Environ Med. 2007;49:1317-1324.

9. Lloyd-Jones D, Adams RJ, Brown TM, et al. Heart disease and stroke statistics— 2010 update: a report from the American Heart Association. Circulation. 2010; 121:e46-e215.

10. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999-2000. JAMA. 2002;288:1723-1727.

11. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA. 2010;303:235-241.

12. Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract. 1998;1:2-4.

13. Coleman K, Austin BT, Brach C, Wagner EH. Evidence on the chronic care model in the new millennium. Health Aff (Millwood). 2009;28:75-85.

14. Ozminkowski RJ, Goetzel RZ, Smith MW, et al. The impact of the Citibank, NA, health management program on changes in employee health risks over time.

J Occup Environ Med. 2000;42:502-511.

15. Soler RE, Leeks KD, Razi S, et al. A systematic review of selected interventions for worksite health promotion. The assessment of health risks with feedback. Am J Prev Med. 2010;38(2 suppl):S237-S262.

16. Kowlessar N, Henke RM, Goetzel RZ, et al. The influence of worksite health promotion program management and implementation structure variables on medical care costs at PPG Industries. J Occup Environ Med. 2010;52:1160-1166.

17. Center for Aging and Population Health Prevention Research Center, University of Pittsburgh. The “10 Keys” to Healthy Aging Resource Guide. June 1, 2011. www12.edc.gsph.pitt.edu/CHA_OAEP/documents/ResourceGuide_062911.pdf.

Accessed October 1, 2010.

18. InfoTech. Wellness Checkpoint. www.wellnesscheckpoint.com/. Accessed October 1, 2010.

19. Thomson Reuters Advantage Suite database. http://thomsonreuters.com/content/ healthcare/pdf/products/advantage_suite_brochure. Accessed October 1, 2010.

20. McCracken S, Hashmi A. Clinically based episode grouping methodology: medical episode grouper. October 2009. Thomson Reuters. http://thomsonreuters.com/ content/healthcare/pdf/white_papers/medical_episode_grouper. Accessed August 26, 2011.

21. Goetzel RZ, Pronk NP. Worksite health promotion: how much do we really know about what works? Am J Prev Med. 2010;38(2 suppl):S223-S225.

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STAKEHOLDER PERSPECTIVE Employers’ Obesity Initiatives in the Workplace: A Wakeup Call for Health Plans Dr Colombi and Mr Wood provide important messages for employers and their supporting health plans.

In their study described in this issue of American Health & Drug Benefits, Dr Colombi and Mr Wood have demonstrated how employer engagement and population-based proactive analyses of employees’ experiences can identify meaningful areas for aligned and coordinated intervention.

HEALTH PLANS: The employer, as a health plan sponsor, is a partner that has a significant role to play in ensuring the effective identification of employees’ risk factors and appropriate disease management.

Such workplace-based functions initiated by employers supplement actions taken by health plans on behalf of the employee. The impact of these activities is important, in part, because these actions represent a population (not an individual patient) level, datasupported tactical application of resources and are not redundant with community-based disease management initiatives that are started after the recognition of a diagnostic claim.

The experience described in this article should serve as a wakeup call for health plans to coordinate and supplement employer initiatives to the financial benefit of employees and the health plan sponsor. To assist in this goal, health plans should develop and make available effective data analytics that will highlight important comorbidities associated with conditions such as obesity to initiate disease management plans that carry greater impact for the patient as a whole rather than reflecting a single-organ system orientation. As employers identify worksites with greater risk (eg, higher obesity rates), this information may be leveraged to greater advantage for health plans that support other groups in the same geographic location.

EMPLOYERS: PPG Industries should be applauded for supporting the use of their data to identify health

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risks in their employees that are normally receiving only a token response from the traditional services provided by health plans. This employer experience demonstrates costs that are silently “accepted” by employers who do not support and promote worksite risk factor identification and modification.

Obesity’s effects on cardiovascular disease progression and on the utilization and cost of care are areas of modifiable expenses. The challenge for the US healthcare system is that the intervention needed is more behavioral than clinical, more preventive than therapeutic, and more population-based than patientapplied. Although employers often hear about the obesity epidemic, the majority of employers fail to recognize the costs to the employer plan sponsor and to their employees for not taking action regarding obesity interventions. These costs affect the employer’s ability to meet business goals and more favorable cost structures in very direct ways. Employees’ good health is good business.

As the prevalence of obesity accelerates beyond 30% of the US population, the cost differentials described in this article will prove increasingly conservative: the actual costs and opportunities will be far greater, because the data in this study reflect on employees who chose to participate in these worksite wellness programs. Many other employees with similar risk factors chose not to participate in such supportive programs, yet they incur excess care utilization and costs. This experience represents the results of a secondary filter not of those who participate in health plan programs but rather of those who are proactively engaged via population-based worksite initiatives.

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Wayne M. Lednar, MD, PhD Global Chief Medical Officer EI du Pont de Nemours, Wilmington, DE

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Knowledge helps empower patients to engage in a heart-healthy lifestyle

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The Upbeat™ program is funded by and content is provided by Daiichi Sankyo, Inc. and Lilly USA, LLC—leaders in healthcare, innovators in life.

CLINICAL

Review ARticle

A Call to Action: Responding to the Future Forecasting of Cardiovascular Disease in America Robert lee Page ii, PharmD, MSPH, FAHA, FccP, FAScP, FASHP, BcPS (AQ cards); vahram Ghushchyan, PhD; Kavita Nair, PhD

Robert Lee Page II

Stakeholder Perspective, page 287

Am Health Drug Benefits.

2011;4(5):280-288 www.AHDBonline.com Disclosures are at end of text

Background: Cardiovascular disease (CVD) continues to be a leading cost driver for payers in the United States. The American Heart Association estimates that more than 75 million individuals nationwide have some form of CVD. Individuals aged 20 to 45 years are developing CVD at higher rates than ever before.

Objectives: To discuss the alarming increase in the rate of CVD in young adults (aged 18-45 years) previously only seen in older adults (aged ≥65 years) and describe the 5 primary risk factors (smoking, obesity, hypertension, diabetes, and dyslipidemia) that contribute to this new trend in the working-age population.

Discussion: Using Medical Expenditure Panel Survey data, this article outlines the increased prevalence of the 3 primary components of CVD—stroke, heart failure, and myocardial infarction—in younger adults and the cost impact on payers and on US society. The examples provided in this article highlight the need for increased efforts by all healthcare stakeholders, and by payers in particular, to develop prevention strategies for CVD risk factors targeted at young adults to curb the alarming rise in CVD among this age-group.

Conclusion: This article provides compelling evidence for the need to institute prevention measures to curb the growing prevalence of CVD risk factors among younger adults in the United States.

D

espite advances in life-saving medical interventions and pharmacotherapies, cardiovascular disease (CVD) continues to be a leading killer in the United States.1 The spectrum of CVD consists of hypertension, chronic heart disease (CHD; including myocardial infarction [MI] and angina), heart failure, and stroke. Based on 2009 data from the American Heart Association (AHA), 76.4 million Americans have been diagnosed with hypertension, 16.3 million have CHD, 5.7 million have heart failure, and 7 million have stroke.2 Beginning in adolescence, CVD can stay dormant for Dr Page is Associate Professor of Clinical Pharmacy and Physical Medicine, School of Pharmacy and Medicine, and Clinical Specialist, Division of Cardiology; Dr Ghushchyan is Research Assistant Professor of Clinical Pharmacy, School of Pharmacy; and Dr Nair is Associate Professor of Clinical Pharmacy, School of Pharmacy, University of Colorado University of Colorado Anschutz Medical Campus, Aurora, CO.

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many years before emerging in adulthood. Among each of the components of CVD, CHD accounts for 1 in every 6 American deaths, heart failure for 1 in every 9 deaths, and stroke for 1 in every 18 deaths.2 Despite these dramatic statistics, CVD mortality rates have begun to decline over the past decade (Figure 1).2,3 These reductions are primarily a result of advances in medical and interventional therapies, as well as to increased acceptance and application of evidence-based guidelines.2,3 In addition, over the past decade the AHA and the American College of Cardiology (ACC) have launched nationwide campaigns that incentivize health systems to improve the overall quality of hospital care through the implementation of CVD quality core measures. Recently, a large population-based study suggested that the age- and sex-adjusted incidence of acute MI exhibited a 24% relative decrease between 1999 and 2008 and that the age- and sex-adjusted 30-day mortality rate after acute MI decreased from 10.5% in 1999 to 7.8% in 2008 (P <.001).4

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Forecasting the Future of CVD: The AHA Policy Statement As patients are living longer and potentially using more healthcare resources, it comes as no surprise that US medical costs for treating CVD have grown at an average annual rate of 6% and now account for about 15% of the increase in overall medical spending.5 To address this problem, the AHA has recently issued a health policy statement to forecast the prevalence and medical costs of CVD and its component diseases through 2030.5 In this statement, data were generated from the 19992006 National Health and Nutrition Examination Survey (NHANES) to project the prevalence of hypertension, CHD, heart failure, and stroke; and data from the US Census Bureau were used to estimate projected population counts from 2010 to 2030. Based on their analysis, the AHA investigators projected that the prevalence of CVD and its component diseases will be increasing over the next 20 years (Figure 2).5 Specifically, they calculated a 9.9% increase from 2010 to 2030 in the prevalence of CVD, along with a 16.6% increase in CHD and a 25% increase in heart failure and stroke.5 This overall increase was primarily driven by an increase in hypertension. These findings correlate to an additional 27 million Americans expected to be diagnosed with hypertension, 8 million with CHD, 4 million with stroke, and 3 million with heart failure —meaning that by 2030, 40.5% of all Americans will suffer from some form of CVD.5

KEY POINTS ➤

➤

➤

➤

➤

➤

➤

➤

The American Heart Association (AHA) estimates that >75 million Americans have some form of cardiovascular disease (CVD), and almost half of the US population will have it by 2030.

The AHA projects a 9.9% increase in the prevalence of CVD by 2030, a 16.6% increase in chronic heart disease, and a 25% increase in heart failure and stroke.

Direct medical costs for CVD are expected to rise from $272.5 billion in 2010 to $818.1 billion in 2030, representing a 3-fold increase.

Young adults aged 20 to 45 years are developing CVD at an alarmingly high rate that was until recently only seen in older adults.

The CVD risk factors once documented in older adults have shifted to young adults aged 20 to 45 years who are developing CVD at an alarmingly high rate.

Because CVD is increasing in younger adults who are in the workforce, employers and payers need to focus their attention on a younger population of adults.

Risk factor modification earlier in life has a greater impact than more significant risk reductions later in life; prevention efforts at a younger age may therefore have a lasting impact later in life.

Instituting preventive measures in young adults may also result in significant cost-savings to payers.

Figure 1 US Deaths from Diseases of the Heart, 1900-2007 1000

Deaths, in thousands

800

600

400

200

0 1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

2007

Year

NOTE: The vertical line marks the beginning in the decline of deaths from heart disease.

Adapted with permission from Roger VL, et al. Circulation. 2011;123:e18-e209.

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Subsequently, as seen in Table 1, total direct medical costs for CVD are expected to rise from $272.5 billion in 2010 to $818.1 billion in 2030, representing a 3-fold increase.5 Because heart failure, CHD, and stroke are debilitating diseases, it is not surprising that indirect costs are also expected to increase from 53% to 80%.

Indirect costs associated with CHD are estimated to account for about 40% of all CVD costs.5 To provide logic behind these drastic projections, the AHA suggests that rapid growth in the aging US population, combined with the growth in per-capita medical expenditures, may be the primary drivers of increased CVD-related costs. The population with the highest costs for CVD will be those aged ≥65 years, with the greatest increase in those aged ≥85 years. Heart failure remains the leading discharge diagnosis for patients aged ≥65 years and has been estimated to account for more than 37% of Medicare spending.6 Unlike heart failure, acute coronary syndrome (ACS), an umbrella term encompassing MI and unstable angina, is common among the working-age population: about 47% of all patients with ACS are younger than age 65 years.7 Results from the Worcester Heart Attack Study show that between 1975 and 2005, the overall incidence of MI was 66 per 100,000 among adults aged 25 to 54 years.8 For employers and payers, patients with ACS impose a substantial direct cost burden, as well as a dramatic indirect cost burden on employers.9,10 In a retrospective analysis of 30,200 patients with ACS, Johnston and colleagues estimated that compared with patients

Figure 2 Projections of Crude CVD Prevalence in the United States, 2010-2030 All CVDa HTN CHD

HF Stroke

45 40

Prevalence, %

35 30 25 20 15 10 5 0 2010

2015

2020

2025

2030

Year a

Includes HTN, CHD, HF, and stroke.

CHD indicates coronary heart disease; CVD, cardiovascular disease; HF, heart failure; HTN, hypertension.

Source: Reference 5.

Table 1 Projected Direct Medical Costs of CVD in the United States, in Billions (2008 dollars) Year

All CVDa

HTN

CHD

HF

Stroke

HTN as risk factorb

2010

$272.5

$69.9

$35.7

$24.7

$28.3

$130.7

2015

$358.0

$91.4

$46.8

$32.4

$38.0

$170.4

2020

$470.3

$119.1

$61.4

$42.9

$51.3

$222.5

2025

$621.6

$155.0

$81.1

$57.5

$70.0

$293.6

2030

$818.1

$200.3

$106.4

$77.7

$95.6

$389.0

200

186

198

215

238

198

Change, %

a Includes HTN, CHD, HF, stroke, as well as cardiac dysrhythmias, rheumatic heart disease, cardiomyopathy, pulmonary heart disease, and other or ill-defined “heart” diseases; does not include HTN as a risk factor. b Includes a portion of the costs of complications associated with HTN, including CHF, CHD, stroke, and other CVDs. The cost of HTN as a risk factor should not be included to calculate the costs of all CVD. CHD indicates coronary heart disease; CVD, cardiovascular disease; HF, heart failure; HTN, hypertension.

Adapted with permission from Heidenreich PA, et al. Circulation. 2011;123:933-944.

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without CHD, the incremental annual direct cost of ACS to employers was $40,671 between 2002 and 2007 (P <.001), and the estimated incremental shortterm disability cost was $999 (P <.001).10 Based on these statistics and the potential impact of healthcare reform, it will likely be payers who will bear the brunt of the economic burden associated with CVD. When approaching this potential costly epidemic, in what population should interventional strategies be targeted to manage these increasing costs?

Addressing an Older Disease in a Newer Generation CVD in Young Adults Data from the Framingham Heart Study and the National Center for Health Statistics have suggested a decline in mortality associated with CHD, particularly in older adults, but the evidence regarding the incidence and case-fatality rates of CHD among young adults has been limited. Recently, Ford and Capewell have demonstrated that the annual estimated percentage change in CHD mortality slowed markedly between 1980 and 2002 in adult men and women aged 35 to 44 years compared with other age-groups (Figure 3).11 The CVDs once documented in older adults have shifted to a younger generation. This unfavorable trend

appears to coincide with an increase in several risk factors associated with CVD, such as smoking, elevated total cholesterol levels, diabetes, hypertension, and obesity.2 Current data suggest that the traditional risk factors for CVD that include serum cholesterol, blood pressure, and cigarette smoking in older adults (aged 40-59 years) are also significantly associated with death from CVD in younger adults (18-39 years).12 With this in mind, payers need to focus their attention not only on the older population (ie, >65 years) but also on a younger population of adults who are now developing CVD much earlier in their lives and carry a much greater risk factor burden than past generations.

The question remains, of the many risk factors for CVD, which should be targeted?

Selected Risk Factors in Young Adults Smoking. The devastation and healthcare costs associated with smoking have been well documented.

Between 2000 and 2004, in young adults aged â&#x2030;Ľ35 years, 32.7% of smoking deaths were tied to CVD.2,13 Despite 4 decades of progress in reducing the prevalence of smoking in the United States, among Americans aged â&#x2030;Ľ18 years, 23.1% of men and 18.3% of women continued to smoke in 2008.2 In addition, the percentage of US adults

Figure 3 Trends in Age-Specific Mortality Rates from Coronary Heart Disease for Men (Triangles) and Women (Squares) 55-64 years 35-44 years

700

Per 100,000 population

40 30 20 10

200 150 100 50 0

200 100 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02

19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02

Per 100,000 population

85+ years

3000 2500 2000 1500 1000 500

7000 6000 5000 4000 3000 2000 1000 0 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02

19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02

Per 100,000 population

19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02

300

8000

3500

0

Year

400

Year

75-84 years

65-74 years

400 200 0

500

Year

Year

1600 1400 1200 1000 800 600

600

0

19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02

0

250

Per 100,000 population

Per 100,000 population

50

Per 100,000 population

45-54 years

60

Year

Year

Reprinted with permission from Ford ES, et al. J Am Coll Cardiol. 2007;50:2128-2132.

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Figure 4 Total Healthcare Expenditures for Healthy Individuals versus Those with a Disease of Interest, 2000-2008 9000

Expenditures, $ (2010 dollars)

8000

$7694

Healthy Disease

7000 6000

$5594 $5140

5000 4000 $2766

3000 $2083

$2325 $2348 $2134

$2156

2000

$2059

1000 0 Obesity

Smoking

Diabetes

Dyslipidemia Hypertension

Disease state

aged ≥18 years who were current smokers did not change significantly from 2005 to 2009.2 Hypertension. Data from the 2007-2008 NHANES suggest that the prevalence of hypertension has increased among US adults aged ≥20 years from approximately 50 million between 1988 and 1994 to approximately 76 million in the period between 2005 and 2008.2 However, this estimate in younger adults is controversial. The 20072008 NHANES reports hypertension among 4% of young adults (aged 24-32 years),2 but the Add Health study now suggests a much higher prevalence of at least 19%.14 Although the health benefits in controlling hypertension through pharmacotherapy are well documented (eg, 35%-40% reduction in stroke, 20%-25% in CHD, and 50% in heart failure), more than 65% of patients with hypertension remain uncontrolled.15 Obesity. Obesity has been correlated with a marked mortality increase in the US population. Even more notable is the excess morbidity associated with being overweight (body mass index [BMI], 25.0-29.9 kg/m2) and with the risk for developing diabetes mellitus and CVD (including CHD, stroke, and heart failure).2 Using NHANES data, Bibbins-Domingo and colleagues estimated that the current number of overweight adolescents will increase the prevalence of obesity among those aged 35 years in 2020 to between 30% and 37% in men and 34% and 44% in women.16 Based on these estimates, the prevalence of CHD will increase to between 5% and 16% by 2035, with more than 100,000 excess cases of CHD attributable to increased obesity.16

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Diabetes. The complications of diabetes can be devastating, particularly in terms of CHD and stroke risk.

Longitudinal analyses from the Framingham Heart Study suggest that the risk factor–adjusted relative risk for CHD was 1.38 (95% confidence interval [CI], 0.99-1.92) times higher and the risk for CHD death was 1.86 (95% CI, 1.17-2.93) times higher for each 10-year increase in the duration of diabetes.17 In addition, the presence of diabetes increases the risk for stroke 2- to 6-fold compared with patients without diabetes.18 Dyslipidemia. An estimated 33.6 million adults aged ≥20 years have total serum cholesterol levels exceeding 240 mg/dL.2 In addition, 8% of Americans aged ≥20 years have undiagnosed dyslipidemia.2,19 Strong epidemiologic data have linked elevated total cholesterol concentrations, particularly the low-density lipoprotein subfraction, to the initial development of CHD.20 During the teenage years, elevated total cholesterol levels can result in predisposition to CHD, cerebrovascular disease, and peripheral vascular disease and eventually lead to CVD.

The Costs of CVD in Young Adults: An Incremental Analysis of Risk Factors The impact of these individual factors on CVD has been described, but the individual impact of these risk factors on total healthcare costs remains unknown. To determine this impact, we used data from the Agency for Healthcare Research and Quality’s Medical Expenditure Panel Survey (MEPS) from 2000 to 2008 to estimate the total costs per person per year for individuals (aged 20-45 years) who have one of the risk factors previously described. We then compared those costs with the expenditures for those without these risk factors (Figure 4).

As shown in Figure 4, the overall costs for patients with diabetes, dyslipidemia, or hypertension are substantially higher than for those without one of these diseases.

Therefore, the impact of risk factors for CVD on total healthcare costs for a younger population is clearly a burden for payers.

The risk factors we specify do not necessarily occur alone in individual patients—≥1 of these 5 risk factors may occur simultaneously. We also used the MEPS data to examine the incremental impact of multiple risk factors (1-5) on the probability of incurring 3 components of CVD—stroke, heart failure, or MI—for individuals aged 20 to 45 years (Table 2). The results show that the odds of developing, in particular, heart failure or MI increase significantly the greater the number of risk factors.

Striking at the Heart of the Problem Models of Prevention Although the statistics are sobering, these projections need not become a reality. As discussed, risk factor iden-

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tification and modification can significantly impact the development of CVD. So far, we have highlighted the need to address CVD in younger adult populations. For example, in the Framingham Heart Study, participants with an optimal level of major risk factors for CVD before age 50 years had a lifetime risk of only 5.2% to 8% for actually developing CVD.21 The absence of major established risk factors by age 50 is associated with a very low lifetime risk for CVD and a longer longevity.21 This study suggests that risk factor modification earlier in life may have a greater impact than more substantial reductions later in life. Prevention efforts that are targeted at one point during the life course may have a lasting impact later in life or even on future generations.21 What if preventive efforts addressing CVD were enforced? Would such policy impact the overall incidence of CVD? The answer appears to be an overwhelming yes. Using data from NHANES for patients aged 20 to 80 years who were potential candidates for CVD preventive efforts, Kahn and colleagues applied the Archimedes model to determine the effect of 11 nationally recommended prevention activities on CVDrelated morbidity, mortality, and costs (Table 3).22 They found that if everyone participated in these recommended preventive activities, MI and stroke would be reduced by 63% and 31%, respectively, over the next 3 decades.22 Assuming more feasible levels of performance, MI and stroke would be reduced 36% and 20%, respectively.22 As seen in Table 3, however, many of these preventive activities appear to be unachievable, especially smoking cessation and reducing BMI below the threshold for obesity.

Grabbing “Low-Hanging Fruit” in Prevention Models Third-party providers have the ability to overcome these barriers for their clients and, in the process, address the problem of rising CVD costs. So where do thirdparty providers begin to address the prevention of CVD? We recommend first tackling 2 of the major risk factors (ie, the low-hanging fruit) that the large national cardiovascular and preventive health organizations and federal and state governments are also addressing—tobacco use and obesity.

Smoking cessation. As of 2011, 48 states and 2960 cities and counties in the United States currently enforce 1 or more forms of no-smoking ordinances; 20 states currently have a statewide 100% smoke-free workplace, restaurant, and bar law.23 With an increase in the implementation of state and county smoking bans, many smokers may be contemplating quitting but need further resources.

Smoking-cessation treatments still remain highly costeffective; however, a strong relationship exists between

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Table 2 Odds Ratio for Having a Stroke, Myocardial Infarction, or Heart Failure, Based on the Number of Risk Factors Number of risk factors

Odds ratioa

95% Confidence interval

1

1.401574

0.9757192-2.013295

2

2.279393

1.554257-3.342839

3

2.992878

1.714301-5.225057

4

3.402792

1.363972-8.489173

5

2.687789

0.5203646-13.88298

1

2.982881

1.778964-5.001553

2

5.426217

3.146884-9.356505

3

14.61261

8.609861-24.80043

4

20.00585

10.30856-38.82542

5

25.74491

7.052921-93.97528

1

1.285253

0.8941822-1.84736

2

3.953156

2.66242-5.869638

3

5.436472

3.33008-8.87523

4

8.499752

4.112478-17.56746

5

13.10736

2.514389-68.32784

Stroke

Myocardial infarction

Heart failure

a

Controlling for total age, sex, race, region, highest education, income, and total number of comorbidities.

the length of behavior counseling sessions, provider-toperson contact, and successful treatment.22 With this in mind, smoking-cessation programs must include comprehensive approaches to quitting rather than just mere coverage of smoking-cessation medications.

One particular example involves the successful implementation of a population-based smoking-cessation program.24 In 2006, based on the Massachusetts healthcare reform law, MassHealth subscribers were allowed two 90day courses of US Food and Drug Administration– approved medications for smoking cessation as well as up to 16 individual or group counseling sessions. From July 1, 2006, to December 31, 2008, 37% (ie, >75,000) of MassHealth members were smokers enrolled in the program.24,25 At 2.5 years after implementation of the program, 26% of MassHealth smokers quit smoking, which resulted in a 38% decrease in hospitalizations for MI, a 17% drop in emergency department and clinic visits for asthma, and a 17% drop in claims for adverse

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Table 3 Summary of Preventive Health Interventions Feasible performance, % achieveda

Intervention Aspirin therapy if 10-year risk of MI ≥10%

50

Lower LDL-C to <160 mg/dL in low-riskb patients

75

c

Lower LDL-C to <130 mg/dL in high-risk patients

70

Lower LDL-C to <100 mg/dL in patients with CAD

70

Lower LDL-C to <100 mg/dL in patients with DM

65

Lower BP to 140/90 mm Hg in patients without DM

75

Lower HbA1c <7.0% in patients with DM

60

Reduce FPG to <110 mg/dL

60

Smoking cessation

30

Reduce weight to BMI <30 kg/m2

20

a

Derived from performance measures from large epidemiologic studies, the Veterans Administration, health plans, and large health systems. b Defined as having 0 or 1 of the following risk factors: blood pressure >140/90 mm Hg; high-density lipoprotein cholesterol <40 mg/dL; family history of MI before age 55 years; male >45 or female >55 years. c Defined as having ≥2 of the risk factors defined for low risk.

BMI indicates body mass index; BP, blood pressure; CAD, coronary artery disease; DM, diabetes mellitus; FPG, fasting plasma glucose; HbA1c, glycated hemoglobin; LDL-C, low-density lipoprotein cholesterol; MI, myocardial infarction.

Adapted with permission from Kahn R, et al. Circulation.

2008;118:576-585.

maternal birth complications.25 For MIs alone, the program resulted in a net savings of $10.5 million, or a $3.07 return on investment for every dollar spent.24-26 Weight-loss programs. Although funding weight-loss and physical activity interventions may not seem conventional to third-party payers, these types of interventions are the centerpiece for the evidence-based recommendations of the AHA, ACC, American Diabetes Association, and the US Preventive Health Services Task Force.27 Between 2005 and 2007, the Partnership for Prevention evaluated the relevant evidence to support the ranking of the health impact and cost-effectiveness of 25 clinical preventive services. Included at the top of the list of services were dietary counseling, which encompassed obesity screening with high-intensity lifestyle counseling for obese patients, and intensive behavioral counseling for patients with hyperlipidemia and other risk factors for CVD.27

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Recently, Rock and colleagues found that a commercial weight-loss program that included free prepared meals and weight-loss incentives produced weight loss and prevented weight regain.28 To address this issue, third-party payers may need to “think outside of the box,” potentially covering personalized, coordinated multidisciplinary weight-loss programs that address patient education and pharmacologic therapies as well as nutrition, diet, and exercise counseling for insured individuals who meet the definition of obesity.

Engaging the Younger Population One of the main barriers to tackling this populationbased problem will be identifying creative and insightful methods to engage the younger population at risk for CVD. In 2011, the American Stroke Association (ASA) questioned 1248 Americans aged 18 to 44 years about their attitudes to health, behavior, and risks of stroke.29 Unfortunately, 43% of those aged 18 to 24 years and 36% of those aged 25 to 34 years were not concerned about CVD compared with only 22% of those aged 35 to 44 years.29 Within the 18- to 34-yearold population, 21% of the women and 31% of the men were “likely to eat fast food,” only one third stated that they were “likely to eat recommended servings of fruits and vegetables,” and about 40% engaged in regular physical activity.29 To overcome this “invincibility” complex, third-party payers will need to collaborate with national partners, such as the Centers for Disease Control and Prevention, the AHA, the ACC, and the ASA, to develop health communications campaigns promoting heart-healthy behaviors. These communication campaigns should be conducted through nontraditional portals, such as social media (eg, Facebook or Twitter), promote incentives, and avoid the use of “scare or judgmental tactics” that may turn away the Generation Y or Generation X audiences. More important, the campaigns should directly engage the population at risk within their own environments (eg, at school).

Conclusions The increasing prevalence of CVD in younger adults aged 20 to 45 years has not been examined in the past.

According to the 2011 AHA Policy Statement focused on the increasing prevalence and costs associated with CVD, 5 primary risk factors—smoking, obesity, hypertension, diabetes, and dyslipidemia—contribute to the development of CVD in young adults. Our analysis of 2000-2008 MEPS data from that population clearly demonstrates the substantial impact of having 1 or more of these risk factors on the likelihood of developing the components of CVD. The examples provided in this

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A Call to Action: Cardiovascular Disease in America

article highlight prevention efforts that may be targeted by using the Archimedes model of prevention. Smoking cessation and obesity, in particular, may provide opportunities for payers and providers to direct their efforts toward the prevention of CVD in the population of young adults. ■ Author Disclosure Statement Dr Page and Dr Ghushchyan reported no conflicts of interest. Dr Nair has received grants from Centocor Ortho Biotech and Novartis and is a Consultant to Centocor Ortho Biotech and Pfizer.

References 1. Kochanek K, Xu J, Murphy SL, et al. Deaths: preliminary data for 2009. Natl Vital Stat Rep. 2011;59:1-51.

2. Roger VL, Go AS, Lloyd-Jones DM, et al, for the American Heart Association.

Heart disease and stroke statistics—2011 update. Circulation. 2011;123:e18-e209.

3. Fox KA, Steg PG, Eagle KA, et al. Decline in rates of death and heart failure in acute coronary syndromes, 1999-2006. JAMA. 2007;297:1892-1900.

4. Yeh RW, Sidney S, Chandra M, et al. Population trends in the incidence and outcomes of acute myocardial infarction. N Engl J Med. 2010;362:2155-2165.

5. Heidenreich PA, Trogdon JG, Khavjou OA, et al, for the American Heart Association. Forecasting the future of cardiovascular disease in the United States.

Circulation. 2011;123:933-944.

6. Page RL II, Strongin K, Millis R, et al. The magnitude of health care resource utilization by Medicare beneficiaries with heart failure. Circulation. 2007;116:II_600.

Abstract 2707.

7. Steg PG, Goldberg RJ, Gore JM, et al. Baseline characteristics, management practices, and in-hospital outcomes of patients hospitalized with acute coronary syndromes in the Global Registry of Acute Coronary Events (GRACE). Am J Cardiol.

2002;90:358-363.

8. McManus DD, Piacentine SM, Lessard D, et al. Thirty-year (1975 to 2005) trends in the incidence rates, clinical features, treatment practices, and short-term outcomes of patients <55 years of age hospitalized with an initial acute myocardial infarction.

Am J Cardiol. 2011;180:477-482. Epub May 31.

9. Zhao Z, Winget M. Economic burden of illness of acute coronary syndromes: medical and productivity costs. BMC Health Serv Res. 2011;11:35.

10. Johnston SS, Curkendall S, Makenbaeva D, et al. The direct and indirect cost burden of acute coronary syndrome. J Occup Environ Med. 2011;53:2-7.

11. Ford ES, Capewell S. Coronary heart disease mortality among young adults in the

U.S. from 1980 through 2002: concealed leveling of mortality rates. J Am Coll Cardiol. 2007;50:2128-2132.

12. Navas-Nacher EL, Colangelo L, Beam C, et al. Risk factors for coronary heart disease in men 18 to 39 years of age. Ann Intern Med. 2001;134:433-439.

13. Centers for Disease Control and Prevention. Smoking-attributable mortality, years of potential life lost, and productivity losses: United States, 2000–2004.

MMWR Morb Mortal Wkly Rep. 2008;57:1226-1228.

14. Nguyen QC, Tabor JW, Entzel PP, et al. Discordance in national estimates of hypertension among young adults. Epidemiology. 2011;22:532-541.

15. Chobanian AV. Shattuck Lecture. The hypertension paradox—more uncontrolled disease despite improved therapy. N Engl J Med. 2009;361:878-887.

16. Bibbins-Domingo K, Coxson P, Pletcher MJ, et al. Adolescent overweight and future coronary heart disease. N Engl J Med. 2007;357:2371-2379.

17. Fox CS, Sullivan L, D’Agostino RB Sr, et al. The significant effect of diabetes duration on coronary heart disease mortality: the Framingham Heart Study. Diabetes Care. 2004;27:704-708.

18. Goldstein LB, Adams R, Becker K, et al, for the Stroke Council of the American Heart Association. Primary prevention of ischemic stroke. Stroke. 2001;32:280-299.

19. Fryar CD, Hirsch R, Eberhardt MS, et al. Hypertension, high serum total cholesterol, and diabetes: racial and ethnic prevalence differences in U.S. adults, 1999– 2006. NCHS Data Brief. 2010;36:1-8.

20. Klag MJ, Ford DE, Mead LA, et al. Serum cholesterol in young men and subsequent cardiovascular disease. N Engl J Med. 1993;328:313-318.

21. Lloyd-Jones DM, Leip EP, Larson MG, et al. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age. Circulation. 2006;113:791-798.

22. Kahn R, Robertson RM, Smith R, et al. The impact of prevention on reducing the burden of cardiovascular disease. Circulation. 2008;118:576-585.

23. Americans for Nonsmokers Rights. Smoke-free list, maps, and data. www.no-smoke. org/goingsmokefree.php?id=519. Accessed August 1, 2011.

24. Land T, Warner D, Paskowsky M, et al. Medicaid coverage for tobacco dependence treatments in Massachusetts and associated decreases in smoking prevalence.

PLoS One. 2010;5:e9770.

25. Land T, Rigotti NA, Levy DE, et al. A longitudinal study of medicaid coverage for tobacco dependence treatments in Massachusetts and associated decreases in hospitalizations for cardiovascular disease. PLoS Med. 2010;7:e1000375.

26. Commonwealth of Massachusetts Health and Human Services. Patrick administration announces positive results from MassHealth smoking cessation benefit.

November 18, 2009. www.mass.gov/?pageID=eohhs2pressrelease&L=1&L0=Home &sid=Eeohhs2&b=pressrelease&f=091118_smoking_cessation&csid=Eeohhs2.

Accessed September 15, 2011.

27. Weintraub WS, Daniels SR, Burke LE, et al, for the American Heart Association. Value of primordial and primary prevention for cardiovascular disease.

Circulation. 2011;124:967-990.

28. Rock CL, Flatt SW, Sherwood NE, et al. Effect of a free prepared meal and incentivized weight loss program on weight loss and weight loss maintenance in obese and overweight women: a randomized controlled trial. JAMA. 2010;304:1803-1810.

29. American Stroke Association. Survey at a glance. www.theheart.org/article/ 1217993.do. Accessed September 6, 2011.

STAKEHOLDER PERSPECTIVE Prevention Efforts before Disease Strikes the Key to a Healthy Population of Young Adults PHYSICIANS: A foundation of the traditional health maintenance organization was to focus on the prevention of disease and maintaining good health.

Improved access to medical resources—including routine physicals, screenings, and vaccinations—would provide for a healthier population, with a reduced risk for acute and chronic diseases. The ability to identify a patient in an earlier stage of disease or a patient on the verge of becoming another “disease statistic” could be

avoided with the implementations of basic interventions by the primary care physician as a gatekeeper for our health system.

As the managed care population has aged, the model has evolved to focus on patients with active disease and efforts to reduce the expense of treating the symptoms and complications associated with chronic disease progression. The availability of a significant number of interventions, including many Continued

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STAKEHOLDER PERSPECTIVE (Continued) medications to treat such patients, has demanded significant resource allocation to manage multiple chronic diseases, such as hypercholesterolemia, hypertension, and diabetes. The increased stress on the body from smoking and obesity significantly contributes to this problem.

PAYERS: The use of tools to identify the high users of healthcare services and patients who are likely to be in need of care management services as a result of significant claims activity provides targets for interventions after the fact. A focus on earlier detection and treatment of disease is a new challenge that health plans face while trying to balance the finances of increased up-front costs and long-term savings.

The need to engage patients in their own well-being and encourage them to lead healthier lifestyles is a common theme in managed care today. Employers actively participate in health and wellness programs offered by insurers, with an emphasis on lifestyle changes and the benefits to good health.

In their Call for Action article in this issue of American Health & Drug Benefits, Page and colleagues focus on the need for prevention by targeting cardio-

vascular disease (CVD) risk factors and a better emphasis on health and wellness for a younger population as critical areas of attention. Smoking, obesity, diabetes, hypertension, and elevated cholesterol levels offer clear targets for health plans to identify these younger, at-risk individuals. The rise in CVD prevalence in the younger population is indeed a concern for health plans as they focus their resources on smokingcessation programs, the importance of diet and nutrition, and the benefits of regular exercise.

PATIENTS: Although the rates of CVD have declined over the past decade in the older population, the cost of treating CVD continues to rise; the reduction of CVD risk factors before the onset of disease offers an essential alternative to costly medical interventions targeting active disease. If individuals, especially younger adults, can decrease their risk factors and improve their health, then the rate of CVD and subsequent events can be significantly reduced.

James T. Kenney, RPh, MBA Pharmacy Operations Manager Harvard Pilgrim Health Care, Wellesley, MA

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Vol 4, No 5

WELCHOL KNOCKS DOWN ®

TWO WITH ONE

FDA-approved, in addition to diet and exercise, for use in adults with T2DM* and primary hyperlipidemia1 Lowers both A1C & LDL-C, without systemic absorption Flexible dosing options: Oral Suspension and Tablet formulations Once-daily dosing

*Type 2 diabetes mellitus.

Welchol for Oral Suspension can now be mixed with fruit juices and diet soft drinks, in addition to water

IMPORTANT INFORMATION ABOUT WELCHOL (colesevelam HCI) Indications Welchol is indicated as an adjunct to diet and exercise to: – reduce elevated low-density lipoprotein cholesterol (LDL-C) in patients with primary hyperlipidemia (Fredrickson Type IIa) as monotherapy or in combination with an hydroxymethylglutaryl-coenzyme (HMG CoA) reductase inhibitor (statin) – improve glycemic control in adults with type 2 diabetes mellitus Important Limitations of Use – Welchol should not be used for glycemic control in type 1 diabetes or for the treatment of diabetic ketoacidosis – Welchol has not been studied in type 2 diabetes as monotherapy or in combination with a dipeptidyl peptidase 4 inhibitor and has not been extensively studied in combination with thiazolidinediones – Welchol has not been studied in Fredrickson Type I, III, IV, and V dyslipidemias Contraindications Welchol is contraindicated in individuals with a history of bowel obstruction, those with serum triglyceride (TG) concentrations of >500 mg/dL, or with a history of hypertriglyceridemia-induced pancreatitis.

Warnings and Precautions The effect of Welchol on cardiovascular morbidity and mortality has not been determined.

Welchol can increase serum TG concentrations particularly when used in combination with sulfonylureas or insulin.

Caution should be exercised when treating patients with TG levels >300 mg/dL.

Welchol may decrease the absorption of fat-soluble vitamins A, D, E, and K. Patients on vitamin supplements should take their vitamins at least 4 hours prior to Welchol. Caution should be exercised when treating patients with a susceptibility to vitamin K or fat-soluble vitamin deficiencies.

Caution should also be exercised when treating patients with gastroparesis, gastrointestinal motility disorders, a history of major gastrointestinal tract surgery, and when treating patients with dysphagia and swallowing disorders.

Welchol reduces gastrointestinal absorption of some drugs. Drugs with a known interaction with colesevelam (cyclosporine, glyburide, levothyroxine, and oral contraceptives [ethinyl estradiol, norethindrone]) should be administered at least 4 hours prior to Welchol. Drugs that have not been tested for interaction with colesevelam, especially those with a narrow therapeutic index, should also be administered at least 4 hours prior to Welchol.

Alternatively, the physician should monitor drug levels of the co-administered drug.

To avoid esophageal distress, Welchol for Oral Suspension should not be taken in its dry form.

Due to tablet size, Welchol for Oral Suspension is recommended for, but not limited to, any patient who has difficulty swallowing tablets.

Phenylketonurics: Welchol for Oral Suspension contains 48 mg phenylalanine per 3.75 gram dose.

Adverse Reactions In clinical trials, the adverse reactions observed in ≥2% of patients, and more commonly with Welchol than placebo, regardless of investigator assessment of causality seen in:

– Adults with Primary Hyperlipidemia were: constipation (11.0% vs 7.0%), dyspepsia (8.3% vs 3.5%), nausea (4.2% vs 3.9%), accidental injury (3.7% vs 2.7%), asthenia (3.6% vs 1.9%), pharyngitis (3.2% vs 1.9%), flu syndrome (3.2% vs 3.1%), rhinitis (3.2% vs 3.1%), and myalgia (2.1% vs 0.4%) – Adult patients with Type 2 Diabetes were: constipation (8.7% vs 2.0%), nasopharyngitis (4.1% vs 3.6%), dyspepsia (3.9% vs 1.4%), hypoglycemia (3.0% vs 2.3%), nausea (3.0% vs 1.4%), and hypertension (2.8% vs 1.6%) Post-marketing experience: Due to the voluntary nature of these reports it is not possible to reliably estimate frequency or establish a causal relationship: – Increased seizure activity or decreased phenytoin levels have been reported in patients receiving phenytoin concomitantly with Welchol – Reduced International Normalized Ratio (INR) has been reported in patients receiving warfarin concomitantly with Welchol – Elevated thyroid-stimulating hormone (TSH) has been reported in patients receiving thyroid hormone replacement therapy Pregnancy Welchol is Pregnancy Category B.

Please see brief summary of the full Prescribing Information about Welchol on next page.

Reference: 1. Welchol (colesevelam HCI). Prescribing Information. Daiichi Sankyo, Inc., Parsippany, NJ, 2011. ©2011 Daiichi Sankyo, Inc.

Printed in USA

07/11

DSWC11001413

www.welchol.com

WELCHOL (colesevelam hydrochloride) Initial U.S. Approval: 2000 BRIEF SUMMARY: See package insert for full prescribing information.

1 INDICATIONS AND USAGE 1.1 Primary Hyperlipidemia WELCHOL is indicated as an adjunct to diet and exercise to reduce elevated low-density lipoprotein cholesterol (LDL-C) in adults with primary hyperlipidemia (Fredrickson Type IIa) as monotherapy or in combination with an hydroxymethyl-glutaryl-coenzyme A (HMG CoA) reductase inhibitor (statin).

WELCHOL is indicated as monotherapy or in combination with a statin to reduce LDL-C levels in boys and postmenarchal girls, 10 to 17 years of age, with heterozygous familial hypercholesterolemia if after an adequate trial of diet therapy the following findings are present: a.LDL-C remains ≥ 190 mg/dL or b.LDL-C remains ≥ 160 mg/dL and • There is a positive family history of premature cardiovascular disease or • Two or more other CVD risk factors are present in the pediatric patient.

Lipid-altering agents should be used in addition to a diet restricted in saturated fat and cholesterol when response to diet and non-pharmacological interventions alone has been inadequate [See Clinical Studies (14.1) in the full prescribing information].

In patients with coronary heart disease (CHD) or CHD risk equivalents such as diabetes mellitus, LDL-C treatment goals are <100 mg/dL. An LDL-C goal of <70 mg/dL is a therapeutic option on the basis of recent trial evidence. If LDL-C is at goal but the serum triglyceride (TG) value is >200 mg/dL, then non-HDL cholesterol (non-HDL-C) (total cholesterol [TC] minus high density lipoprotein cholesterol [HDL-C]) becomes a secondary target of therapy. The goal for non-HDL-C in persons with high serum TG is set at 30 mg/dL higher than that for LDL-C. 1.2 Type 2 Diabetes Mellitus WELCHOL is indicated as an adjunct to diet and exercise to improve glycemic control in adults with type 2 diabetes mellitus [See Clinical Studies (14.2) in the full prescribing information].

Diabetes mellitus is considered a CHD risk equivalent. In addition to glycemic control, intensive lipid control is warranted [See Indications and Usage (1.1) and Warnings and Precautions (5.2)].

1.3 Important Limitations of Use • WELCHOL should not be used for the treatment of type 1 diabetes or for the treatment of diabetic ketoacidosis.

• WELCHOL has not been studied in type 2 diabetes as monotherapy or in combination with a dipeptidyl peptidase 4 inhibitor and has not been extensively studied in combination with thiazolidinediones.

• WELCHOL has not been studied in Fredrickson Type I, III, IV, and V dyslipidemias.

• WELCHOL has not been studied in children younger than 10 years of age or in pre-menarchal girls.

4 CONTRAINDICATIONS WELCHOL is contraindicated in patients with • A history of bowel obstruction [See Warnings and Precautions (5.4)] • Serum TG concentrations >500 mg/dL [See Warnings and Precautions (5.2)]

• A history of hypertriglyceridemia-induced pancreatitis [See Warnings and Precautions (5.2)] 5WARNINGS AND PRECAUTIONS 5.1 General The effect of WELCHOL on cardiovascular morbidity and mortality has not been determined.

5.2 Serum Triglycerides WELCHOL, like other bile acid sequestrants, can increase serum TG concentrations.

WELCHOL had small effects on serum TG (median increase 5% compared to placebo) in trials of patients with primary hyperlipidemia [See Adverse Reactions (6.1) and Clinical Studies (14.1) in the full prescribing information].

In clinical trials in patients with type 2 diabetes, greater increases in TG levels occurred when WELCHOL was used in combination with sulfonylureas (median increase 18% compared to placebo in combination with sulfonylureas) and when WELCHOL was used in combination with insulin (median increase 22% compared to placebo in combination with insulin) [See Adverse Reactions (6.1) and Clinical Studies (14.2) in the full prescribing information]. Hypertriglyceridemia of sufficient severity can cause acute pancreatitis. The long-term effect of hypertriglyceridemia on the risk of coronary artery disease is uncertain. In patients with type 2 diabetes, the effect of WELCHOL on LDL-C levels may be attenuated by WELCHOL’s effects on TG levels and a smaller reduction in non-HDL-C compared to the reduction in LDL-C. Caution should be exercised when treating patients with TG levels greater than 300 mg/dL. Because most patients in the WELCHOL clinical trials had baseline TG <300 mg/dL, it is unknown whether patients with more uncontrolled baseline hypertriglyceridemia would have greater increases in serum TG levels with WELCHOL. In addition, the use of WELCHOL is contraindicated in patients with TG levels >500 mg/dL [See Contraindications (4)]. Lipid parameters, including TG levels and non-HDL-C, should be obtained before starting WELCHOL and periodically thereafter.

WELCHOL should be discontinued if TG levels exceed 500 mg/dL or if the patient develops hypertriglyceridemiainduced pancreatitis [See Adverse Reactions (6.1)].

5.3 Vitamin K or Fat-Soluble Vitamin Deficiencies Precautions Bile acid sequestrants may decrease the absorption of fat-soluble vitamins A, D, E, and K. No specific clinical studies have been conducted to evaluate the effects of WELCHOL on the absorption of co-administered dietary or supplemental vitamin therapy. In non-clinical safety studies, rats administered colesevelam hydrochloride at doses greater than 30-fold the projected human clinical dose experienced hemorrhage from vitamin K deficiency. Patients on oral vitamin supplementation should take their vitamins at least 4 hours prior to WELCHOL. Caution should be exercised when treating patients with a susceptibility to deficiencies of vitamin K (e.g., patients on warfarin, patients with malabsorption syndromes) or other fat-soluble vitamins.

5.4 Gastrointestinal Disorders Because of its constipating effects, WELCHOL is not recommended in patients with gastroparesis, other gastrointestinal motility disorders, and in those who have had major gastrointestinal

tract surgery and who may be at risk for bowel obstruction. Because of the tablet size, WELCHOL Tablets can cause dysphagia or esophageal obstruction and should be used with caution in patients with dysphagia or swallowing disorders.

To avoid esophageal distress, WELCHOL for Oral Suspension should not be taken in its dry form. Always mix WELCHOL for Oral Suspension with water, fruit juice, or diet soft drinks before ingesting.

5.5 Drug Interactions WELCHOL reduces gastrointestinal absorption of some drugs. Drugs with a known interaction with colesevelam should be administered at least 4 hours prior to WELCHOL. Drugs that have not been tested for interaction with colesevelam, especially those with a narrow therapeutic index, should also be administered at least 4 hours prior to WELCHOL. Alternatively, the physician should monitor drug levels of the coadministered drug [See Drug Interactions (7) and Clinical Pharmacology (12.3) in the full prescribing information].

5.6 Phenylketonurics WELCHOL for Oral Suspension contains 24 mg phenylalanine per 1.875 gram packet and 48 mg phenylalanine per 3.75 gram packet [See Description (11) in the full prescribing information].

6 ADVERSE REACTIONS 6.1 Clinical Studies Experience Because clinical studies are conducted under widely varying conditions, adverse reaction rates observed in the clinical studies of a drug cannot be directly compared to rates in clinical studies of another drug and may not reflect the rates observed in practice.

In the lipid-lowering trials, 807 adult patients received at least one dose of WELCHOL (total exposure 199 patientyears). In the type 2 diabetes trials, 566 patients received at least one dose of WELCHOL (total exposure 209 patient-years).

In clinical trials for the reduction of LDL-C, 68% of patients receiving WELCHOL vs. 64% of patients receiving placebo reported an adverse reaction.

In clinical trials of type 2 diabetes, 60% of patients receiving WELCHOL vs. 56% of patients receiving placebo reported an adverse reaction.

Primary Hyperlipidemia: In 7 doubleblind, placebo-controlled, clinical trials, 807 patients with primary hyperlipidemia (age range 18-86 years, 50% women, 90% Caucasians, 7% Blacks, 2% Hispanics, 1% Asians) and elevated LDL-C were treated with WELCHOL 1.5 g/day to 4.5 g/day from 4 to 24 weeks.

Table 1 Placebo-Controlled Clinical Studies of WELCHOL for Primary Hyperlipidemia: Adverse Reactions Reported in ≥2% of Patients and More Commonly than in Patients Given Placebo, Regardless of Investigator Assessment of Causality Number of Patients (%) WELCHOL Placebo N = 807 N = 258 Constipation 89 (11.0) 18 (7.0) Dyspepsia 67 (8.3) 9 (3.5) Nausea 34 (4.2) 10 (3.9) Accidental injury 30 (3.7) 7 (2.7) Asthenia 29 (3.6) 5 (1.9) Pharyngitis 26 (3.2) 5 (1.9) Flu syndrome 26 (3.2) 8 (3.1) Rhinitis 26 (3.2) 8 (3.1) Myalgia 17 (2.1) 1 (0.4)

Pediatric Patients 10 to 17 Years of Age: In an 8-week double-blind, placebo-controlled study boys and post-menarchal girls, 10 to 17 years of age, with heterozygous familial hypercholesterolemia (heFH) (n=192), were treated with WELCHOL Tablets (1.9-3.8 g, daily) or placebo tablets [See Clinical Studies (14.1) in the full prescribing information].

Table 2 Placebo-Controlled Clinical Study of WELCHOL for Primary Hyperlipidemia in heFH Pediatric Patients: Adverse Reactions Reported in ≥2% of Patients and More Commonly than in Patients Given Placebo, Regardless of Investigator Assessment of Causality Number of Patients (%) WELCHOL Placebo N = 129 N = 65 Nasopharyngitis 8 (6.2) 3 (4.6) Headache 5 (3.9) 2 (3.1) Fatigue 5 (3.9) 1 (1.5) Creatine Phosphokinase Increase 3 (2.3) 0 (0.0) Rhinitis 3 (2.3) 0 (0.0) Vomiting 3 (2.3) 1 (1.5) The reported adverse reactions during the additional 18-week open-label treatment period with WELCHOL 3.8 g per day were similar to those during the double-blind period and included headache (7.6%), nasopharyngitis (5.4%), upper respiratory tract infection (4.9%), influenza (3.8%), and nausea (3.8%) [See Clinical Studies (14.1) in the full prescribing information].

Type 2 Diabetes Mellitus: The safety of WELCHOL in patients with type 2 diabetes mellitus was evaluated in 4 double-blind, 12-26 week, placebo-controlled clinical trials. These trials involved 1128 patients (566 patients on WELCHOL; 562 patients on placebo) with inadequate glycemic control on metformin, sulfonylurea, or insulin when these agents were used alone or in combination with other anti-diabetic agents. Upon completion of the pivotal trials, 492 patients entered a 52-week open-label uncontrolled extension study during which all patients received WELCHOL 3.8 g/day while continuing background treatment with metformin, sulfonylurea, or insulin alone or in combination with other anti-diabetic agents.

A total of 6.7% of WELCHOL-treated patients and 3.2% of placebo-treated patients were discontinued from the diabetes trials due to adverse reactions.

This difference was driven mostly by gastrointestinal adverse reactions such as abdominal pain and constipation.

One patient in the pivotal trials discontinued due to body rash and mouth blistering that occurred after the first dose of WELCHOL, which may represent a hypersensitivity reaction to WELCHOL. Table 3 Placebo-Controlled Clinical Studies of WELCHOL Add-on Combination Therapy with Metformin, Insulin, Sulfonylureas: Adverse Reactions Reported in ≥2% of Patients and More Commonly than in Patients Given Placebo, Regardless of Investigator Assessment of Causality Number of Patients (%) WELCHOL Placebo N = 566 N = 562 Constipation 49 (8.7) 11 (2.0) Nasopharyngitis 23 (4.1) 20 (3.6) Dyspepsia 22 (3.9) 8 (1.4) Hypoglycemia 17 (3.0) 13 (2.3) Nausea 17 (3.0) 8 (1.4) Hypertension 16 (2.8) 9 (1.6)

Hypertriglyceridemia: Patients with fasting serum TG levels above 500 mg/dL were excluded from the diabetes clinical trials.

In the phase 3 diabetes trials, 637 (63%) patients had baseline fasting serum TG levels less than 200 mg/dL, 261 (25%) had baseline fasting serum TG levels between 200 and 300 mg/dL, 111 (11%) had baseline fasting serum TG levels between 300 and 500 mg/dL, and 9 (1%) had fasting serum TG levels greater than or equal to 500 mg/dL. The median baseline fasting TG concentration for the study population was 172 mg/dL; the median post-treatment fasting TG was 195 mg/dL in the WELCHOL group and 177 mg/dL in the placebo group.

WELCHOL therapy resulted in a median placebo-corrected increase in serum TG of 5% (p=0.22), 22% (p<0.001), and 18% (p<0.001) when added to metformin, insulin and sulfonylureas, respectively [See Warnings and Precautions (5.2) and Clinical Studies (14.2) in the full prescribing information]. In comparison, WELCHOL resulted in a median increase in serum TG of 5% compared to placebo (p=0.42) in a 24-week monotherapy lipid-lowering trial [See Clinical Studies (14.1) in the full prescribing information].

Treatment-emergent fasting TG concentrations ≥500 mg/dL occurred in 4.1% of WELCHOL-treated patients compared to 2.0% of placebo-treated patients. Among these patients, the TG concentrations with WELCHOL (median 604 mg/dL; interquartile range 538-712 mg/dL) were similar to that observed with placebo (median 644 mg/dL; interquartile range 574-724 mg/dL). Two (0.4%) patients on WELCHOL and 2 (0.4%) patients on placebo developed TG elevations ≥1000 mg/dL. In all WELCHOL clinical trials, including studies in patients with type 2 diabetes and patients with primary hyperlipidemia, there were no reported cases of acute pancreatitis associated with hypertriglyceridemia.

It is unknown whether patients with more uncontrolled, baseline hypertriglyceridemia would have greater increases in serum TG levels with WELCHOL [See Contraindications (4) and Warnings and Precautions (5.2)].

Cardiovascular adverse events: During the diabetes clinical trials, the incidence of patients with treatment-emergent serious adverse events involving the cardiovascular system was 3% (17/566) in the WELCHOL group and 2% (10/562) in the placebo group. These overall rates included disparate events (e.g., myocardial infarction, aortic stenosis, and bradycardia); therefore, the significance of this imbalance is unknown.

Hypoglycemia: Adverse events of hypoglycemia were reported based on the clinical judgment of the blinded investigators and did not require confirmation with fingerstick glucose testing. The overall reported incidence of hypoglycemia was 3.0% in patients treated with WELCHOL and 2.3% in patients treated with placebo. No WELCHOL treated patients developed severe hypoglycemia.

6.2 Post-marketing Experience The following additional adverse reactions have been identified during post-approval use of WELCHOL. Because these reactions are reported voluntarily from a population of uncertain size, it is generally not possible to reliably estimate their frequency or establish a causal relationship to drug exposure.

c Drug Interactions with concomitant Cyclosporine levels should be monitored Type 2 Diabetes Mellitus: Of the 1128 patients enrolled in the four diabetes WELCHOL administration include: and, based on theoretical grounds, studies, 249 (22%) were ≥65 years old, cyclosporine should be administered at • Increased seizure activity or decreased and 12 (1%) were ≥75 years old. In these least 4 hours prior to WELCHOL. phenytoin levels in patients receiving trials, WELCHOL 3.8 g/day or placebo was phenytoin. Phenytoin should be In an in vivo drug interaction study, added onto background anti-diabetic administered 4 hours prior to WELCHOL. WELCHOL and warfarin coadministration • Reduced International Normalized Ratio had no effect on warfarin drug levels. This therapy. No overall differences in safety or effectiveness were observed between the (INR) in patients receiving warfarin study did not assess the effect of elderly and younger patients, but greater therapy. In warfarin-treated patients, INR WELCHOL and warfarin coadministration sensitivity of some older individuals should be monitored frequently during on INR. In postmarketing reports, cannot be ruled out.

WELCHOL initiation then periodically concomitant use of WELCHOL and thereafter. warfarin has been associated with reduced 8.6 Hepatic Impairment • Elevated thyroid-stimulating hormone INR. Therefore, in patients on warfarin No special considerations or dosage (TSH) in patients receiving thyroid therapy, the INR should be monitored adjustments are recommended when hormone replacement therapy. Thyroid before initiating WELCHOL and frequently WELCHOL is administered to patients hormone replacement should be enough during early WELCHOL therapy to with hepatic impairment. administered 4 hours prior to WELCHOL ensure that no significant alteration in INR [See Drug Interactions (7)]. occurs. Once the INR is stable, continue to 8.7 Renal Impairment Type 2 Diabetes Mellitus: Of the 1128 Gastrointestinal Adverse Reactions monitor the INR at intervals usually patients enrolled in the four diabetes recommended for patients on warfarin.

Bowel obstruction (in patients with a studies, 696 (62%) had mild renal history of bowel obstruction or resection), [See Post-marketing Experience (6.2)] insufficiency (creatinine clearance [CrCl] dysphagia or esophageal obstruction 8 USE IN SPECIFIC POPULATIONS 50-<80 mL/min), 53 (5%) had moderate (occasionally requiring medical 8.1 Pregnancy renal insufficiency (CrCl 30-<50 mL/ min), intervention), fecal impaction, pancreatitis, and none had severe renal insufficiency Pregnancy Category B. There are no abdominal distension, exacerbation of (CrCl <30 mL/min), as estimated from adequate and well-controlled studies of hemorrhoids, and increased baseline serum creatinine using the colesevelam use in pregnant women. transaminases.

Modification of Diet in Renal Disease Animal reproduction studies in rats and Laboratory Abnormalities rabbits revealed no evidence of fetal harm. (MDRD) equation. No overall differences Hypertriglyceridemia in safety or effectiveness were observed Requirements for vitamins and other between patients with CrCl <50 mL/min nutrients are increased in pregnancy.

7 DRUG INTERACTIONS (n=53) and those with a CrCl ≥50 mL/min However, the effect of colesevelam on the Table 4 lists the drugs that have been (n=1075). absorption of fat-soluble vitamins has not tested in in vitro binding or in vivo drug been studied in pregnant women. This interaction studies with colesevelam 10 OVERDOSAGE drug should be used during pregnancy and/or drugs with postmarketing reports Doses of WELCHOL in excess of 4.5 g/day only if clearly needed. consistent with potential drug-drug have not been tested. Because WELCHOL interactions. Orally administered drugs In animal reproduction studies, is not absorbed, the risk of systemic that have not been tested for interaction colesevelam revealed no evidence of toxicity is low. However, excessive doses with colesevelam, especially those with a fetal harm when administered to rats of WELCHOL may cause more severe local narrow therapeutic index, should also be and rabbits at doses 50 and 17 times gastrointestinal effects (e.g., constipation) administered at least 4 hours prior to the maximum human dose, respectively. than recommended doses.

WELCHOL. Alternatively, the physician Because animal reproduction studies are should monitor drug levels of the conot always predictive of human response, administered drug. this drug should be used in pregnancy only if clearly needed.

Table 4 Drugs Tested in In Vitro Binding 8.3 Nursing Mothers or In Vivo Drug Interaction Testing or Colesevelam hydrochloride is not expected With Post-Marketing Reports to be excreted in human milk because colesevelam hydrochloride is not absorbed systemically from the gastrointestinal tract. cyclosporinec, a glyburide , 8.4 Pediatric Use a Drugs with a levothyroxine , and The safety and effectiveness of WELCHOL known interaction oral contraceptives as monotherapy or in combination with a with colesevelama containing ethinyl statin were evaluated in children, 10 to 17 estradiol and years of age with heFH [See Clinical norethindrone Studies (14.1) in the full prescribing information]. The adverse reaction profile Drugs with was similar to that of patients treated with postmarketing placebo. In this limited controlled study, reports consistent there were no significant effects on with potential phenytoina, growth, sexual maturation, fat-soluble drug-drug warfarinb vitamin levels or clotting factors in the interactions when adolescent boys or girls relative to placebo coadministered [See Adverse Reactions (6.1)]. with WELCHOL Due to tablet size, WELCHOL for Oral Suspension is recommended for use in the cephalexin, pediatric population. Dose adjustments are ciprofloxacin, not required when WELCHOL is administered digoxin, warfarinb, to children 10 to 17 years of age. fenofibrate, Drugs that do lovastatin, WELCHOL has not been studied in not interact with metformin, children younger than 10 years of age colesevelam metoprolol, or in pre-menarchal girls. based on in vitro pioglitazone, 8.5 Geriatric Use or in vivo testing quinidine, Primary Hyperlipidemia: Of the 1350 repaglinide, patients enrolled in the hyperlipidemia valproic acid, clinical studies, 349 (26%) were verapamil ≥65 years old, and 58 (4%) were ≥75 years old. No overall differences in safety a Should be administered at least 4 hours or effectiveness were observed between prior to WELCHOL these subjects and younger subjects, b No significant alteration of warfarin drug and other reported clinical experience Daiichi Sankyo, Inc. has not identified differences in responses Marketed by: levels with warfarin and WELCHOL Parsippany, New Jersey coadministration in an in vivo study which between the elderly and younger patients, 07054 did not evaluate warfarin pharmacodynamics but greater sensitivity of some older (INR). [See Post-marketing Experience (6.2)] individuals cannot be ruled out.

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REVIEW ARTICLE

Atypical Antipsychotics and Metabolic Syndrome in Patients with Schizophrenia: Risk Factors, Monitoring, and Healthcare Implications Henry J. Riordan, PhD; Paola Antonini, MD, PhD; Michael F. Murphy, MD, PhD

Stakeholder Perspective, page 301

Am Health Drug Benefits.

2011;4(5):292-302 www.AHDBonline.com Disclosures are at end of text

Background: Metabolic syndrome is a leading cause of morbidity and mortality in patients with schizophrenia, with a prevalence rate double that of nonpsychiatric populations. Given the amount of evidence suggesting a link between atypical antipsychotic medications and metabolic syndrome, several agencies have recommended regular clinical monitoring of weight, symptoms of hyperglycemia, and glucose in chronically medicated patients with schizophrenia.

Objectives: To summarize the current literature on atypical antipsychotic-induced metabolic syndrome in patients with schizophrenia, outline some of the molecular mechanisms behind this syndrome, identify demographic and disease-related risk factors, and describe cost-effective methods for surveillance.

Discussion: The differential prevalence of metabolic syndrome associated with various atypical antipsychotic medications has been evidenced across numerous studies, with higher effects seen for certain antipsychotic medications on weight gain, waist circumference, fasting triglyceride level, and glucose levels. Given the association of these symptoms, all atypical antipsychotic medications currently include a warning about the risk of hyperglycemia and diabetes, as well as suggestions for regular monitoring. Despite this, very little data are available to support adherence to these monitoring recommendations.

Lack of awareness and resources, diffusion of responsibility, policy implementation, and organizational structure have all been implicated.

Conclusion: The treatment of schizophrenia involves a balance in terms of risks and benefits. Failing to treat because of risk for complications from metabolic syndrome may place the patient at a higher risk for more serious health outcomes. Supporting programs aimed at increasing monitoring of simple laboratory and clinical measures associated with metabolic syndrome may decrease important risk factors, improve patientsâ&#x20AC;&#x2122; quality of life, and reduce healthcare costs.

D

espite treatment advances in prevention, cardiovascular disease (CVD) remains the leading cause of mortality globally. CVD is responsible for 30% of all deaths and represents one of the leading longterm health considerations in the population as a whole.1 CVD is also the most common cause of natural mortality in schizophrenia, accounting for a total of 34% of deaths Dr Riordan is Senior Vice President of Medical and Scientific Affairs; Dr Antonini is Senior Vice President of Medical and Scientific Affairs, Drug Safety; and Dr Murphy is Chief Medical and Scientific Officer, Worldwide Clinical Trials, King of Prussia, PA.

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among male patients and 31% of deaths in female patients and is surpassed only by suicide.2 In fact, it has been estimated that the prevalence of dyslipidemia, hypertension, obesity, and type 2 diabetes is approximately 1.5 to 2 times higher in individuals with schizophrenia and other serious mental illness compared with the general population.3 Although the exact prevalence of metabolic syndrome in adults with schizophrenia varies greatly (between 20% and 60%), common estimates typically place this at twice that of the normal healthy population.4

The Scope of the Problem Given that schizophrenia occurs in approximately

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1.1% of the population aged >18 years, or 2.2 million Americans, this has a significant impact on healthcare utilization and expenditures. Increased awareness of metabolic syndrome as a risk factor for CVD, as well as associated guidance for screening, monitoring, and treatment are urgently needed.

This article concentrates on issues germane to adult schizophrenia, but excessive morbidity and mortality linked to metabolic syndrome and CVD is not limited to this population. These concerns also affect adolescents with schizophrenia, as well as adults and adolescents with severe mental illness such as bipolar disease and other psychiatric diagnoses who may be prescribed atypical, or second-generation, antipsychotic medications.

Adverse events associated with the use of atypical antipsychotic medications are thought to be largely, but not singularly, contributory to cardiometabolic and endocrine side effects constituting metabolic syndrome; and children and adolescents receiving atypical antipsychotic medications are particularly vulnerable to these effects.5 It should be noted that in addition to psychotic disorders, atypical antipsychotic medications are often prescribed off-label for the treatment of a variety of pediatric and adult disorders that are associated with aggressive and disruptive behaviors, such as pervasive developmental disorder, disruptive behavior disorders, mental retardation, severe attention-deficit/hyperactivity disorder, tic disorders, obsessive-compulsive disorder, and Alzheimer’s disease. In these indications, the risks of eventually developing metabolic syndrome have to be judged against the more immediate risks of the aggressive behavior in terms of harm to the patient and others.

As noted, the link between schizophrenia and CVD is typically viewed in terms of metabolic syndrome, which is merely a combination of medical risk factors and disorders. Clinical criteria for what constitutes metabolic syndrome are diverse, with the most widely adopted criteria created by the World Health Organization (WHO), the European Group for the Study of Insulin Resistance, and the National Cholesterol Education Program Adult Treatment Panel (NCEP ATP) III. All these organizations agree that the core components of metabolic syndrome include obesity, insulin resistance, dyslipidemia, and hypertension. However, they differ in how they apply criteria to identify symptom clusters.

The WHO and NCEP ATP III define metabolic syndrome on the basis of easily measured clinical features and laboratory measures. According to the International Diabetes Federation definition, criteria for metabolic syndrome include central obesity plus any 2 of the following 4 factors: elevated triglyceride level, reduced high-density lipoprotein cholesterol, elevated blood pressure (BP), and

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KEY POINTS ➤

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Cardiovascular disease (CVD) is the most common cause of natural mortality in schizophrenia.

Given that schizophrenia occurs in approximately 1.1% of the adult population, or 2.2 million Americans, this has a significant impact on healthcare utilization and expenditures.

Side effects associated with atypical antipsychotics are thought to contribute significantly to cardiometabolic and endocrine adverse events constituting metabolic syndrome.

Metabolic syndrome differences among various antipsychotic agents have substantial cost implications for society. Direct medical costs associated with macrovascular complications and hyperglycemia can become considerable.

Ongoing patient monitoring of simple laboratory and clinical measures may help decrease important adverse events in multiple organ systems and ultimately improve patients’ quality of life and reduce healthcare costs.

Increased awareness of metabolic syndrome as a risk factor for CVD is urgently needed.

elevated fasting plasma glucose (FPG) or previously diagnosed type 2 diabetes (Table 1).6

Mechanisms Underlying Metabolic Syndrome in Schizophrenia The putative mechanisms linking atypical antipsychotic medications to metabolic syndrome are multifactorial, and likely include the interplay of dopamine, histamine, orexigenic (anabolic) neuropeptides, adrenergic and muscarinic receptors, and failed glucose homeostasis, as well as the interaction of these with modifiable and nonmodifiable risk factors.7 On a clinically relevant level, weight gain has been a well-known side effect of atypical antipsychotic medications, although references to excessive weight gain exist for first-generation antipsychotic agents, such as chlorpromazine, as well.

Sedentary lifestyle and other risk factors, such as smoking and poor diet, may be contributory; however, atypical antipsychotic agents induce changes in weight that are primarily responsible for changes in glucose metabolism. There is also some evidence that impairments in glucose metabolism may be independent of adiposity, as glucose and lipid metabolism abnormalities may occur without weight gain.8,9 Furthermore, weight gain tends to be generally observable within the first few months of treatment,

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and increases at that time may not be dose-dependent.

Individuals with low body mass index (BMI) at baseline are particularly vulnerable to these effects. Weight gain, especially when manifested as intra-abdominal

Weight gain, especially when manifested as intra-abdominal obesity, plays a significant role in the development of metabolic syndrome and remains a significant long-term health issue in patients with schizophrenia. obesity (often operationalized as increased waist circumference), plays a significant role in the development of metabolic syndrome and remains a significant long-term health issue with implications for overall quality of life in patients with schizophrenia.

Risk Factors There are numerous risk factors that influence the

prevalence of metabolic syndrome in schizophrenia, some of which are modifiable. Variables as diverse as genetic polymorphisms, the unique pharmacology of atypical antipsychotic agents, and lifestyle factors (eg, physical activity, support system, cigarette smoking, and alcohol and drug abuse) also appear to moderate atypical antipsychotic–induced metabolic syndrome.9 Racial and ethnic differences in the presentation of metabolic syndrome are well-described. For example, a positive metabolic syndrome screen for blacks and whites may be associated with increased risk for CVD, whereas a positive metabolic screen for Hispanics and Filipino Americans may be associated with increased risk for diabetes. Furthermore, increased waist circumference has been reported in persons with BMI values that fell well within the “normal” ranges for blacks, Asian Americans, and Hispanics, suggesting that these populations may be at intrinsically increased risk for metabolic syndrome.10 The reasons for these disparities are varied but suggest potential genotypic differences in the applicability of risk factors that constitute metabolic syndrome. Recent pharmacogenetic research has identified genetic factors related to variability in antipsychotic

Table 1 Core Criteria for Diagnosing Metabolic Syndrome International Diabetes Federation (2006)1 Central obesity—defined as waist circumferencea with ethnicity-specific values—plus any 2 of the following: •

Raised triglycerides: ≥150 mg/dL (1.7 mmol/L), or specific treatment for this lipid abnormality

•

Reduced HDL-C: <40 mg/dL (1.03 mmol/L) in men, <50 mg/dL (1.29 mmol/L) in women, or specific treatment for this lipid abnormality

•

Systolic BP ≥130 or diastolic BP ≥85 mm Hg, or treatment of previously diagnosed hypertension

•

FPG ≥100 mg/dL (5.6 mmol/L), or previously diagnosed type 2 diabetes; glucose tolerance test strongly recommended (but not necessary) for FPG >5.6 mmol/L or 100 mg/dL

US National Cholesterol Education Program Adult Treatment Panel III (2001)2 At least 3 of the following: •

Central obesity: waist circumference >102 cm or 40 in (men), >88 cm or 35 in (women)

•

Dyslipidemia: triglycerides ≥1.7 mmol/L (≥150 mg/dL)

•

Dyslipidemia: HDL-C <40 mg/dL (men), <50 mg/dL (women)

•

BP: ≥130/85 mm Hg

•

FPG: ≥110 mg/dL

a

If BMI is >30 kg/m², central obesity can be assumed and waist circumference does not need to be measured.

BMI indicates body mass index; BP, blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol.

1. Adapted with permission from the International Diabetes Federation. The IDF consensus worldwide definition of the metabolic syndrome. 2006. www.idf.org/webdata/docs/IDF_Meta_def_final.pdf.

2. Source: US Department of Health and Human Services. National Cholesterol Education Program: ATP III Guidelines At-A-Glance Quick Desk Reference. May 2001; publication no 01-2205. www.nhlbi.nih.gov/guidelines/ cholesterol/atglance.pdf.

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drug response, including therapeutic response and adverse events.11 In an effort to clarify a potential genetic substrate, researchers examined a group of severely mentally ill patients receiving antipsychotic medications and selected genes that possibly could serve as candidates for future studies of the direct effects of some antipsychotic medications on hyperlipidemia, hypertriglyceridemia, or hypercholesterolemia.12 They conducted a search for single-nucleotide polymorphisms (SNPs) associated with these direct effects that are not explained by obesity. It was hypothesized that olanzapine, quetiapine, and chlorpromazine may increase lipids directly, whereas other antipsychotic medications not associated with similar clinical presentations would serve as control medications. A total of 165 patients taking olanzapine, quetiapine, or chlorpromazine were compared with 192 control patients taking other antipsychotic medications. A cross-sectional sample of these 357 patients was genotyped using a DNA microarray with 384 SNPs. After initial nondirected candidate selection, a directed search identified 3 genes that may be contributory: acetyl-coenzyme A carboxylase alpha (ACACA) SNP in the hypertriglyceridemia model, and neuropeptide Y (NPY) and acetyl-coenzyme A carboxylase beta (ACACB) in the hypercholesterolemia model. This approach suggested that ACACA, ACACB, and NPY genes may be good candidates for studies of the direct effects of some antipsychotic agents on hyperlipidemia; as such, these genes may be promising candidates for future studies.

Obviously, the pharmacologic properties of atypical antipsychotic medications are also contributory, and a recent study suggested that variations in genes encoding for receptor proteins mediating the antipsychotic effect could also be candidates (such as HTR2C polymorphisms). Researchers investigated 4 HTR2C genetic variants in 112 patients with schizophrenia who were mainly using clozapine, olanzapine, and risperidone, and reported that 3 of the 4 HTR2C polymorphisms were associated with an increased risk of metabolic syndrome.13

Choice of Atypical Antipsychotics Differential metabolic profiles associated with several common atypical antipsychotic medications were suggested by the retrospective literature,14 and many prospective trials have confirmed the association.

However, even untreated patients suffering from schizophrenia are at an increased risk for developing many medical conditions classically associated with metabolic syndrome, and the interaction of antipsychotic treatment and disease with environmental factors has been incompletely explored. Nevertheless, differential effects

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across compounds have been described regardless of potential confounding variables.

For example, as part of the Clinical Antipsychotic Trials in Intervention Effectiveness (CATIE) of more than 600 patients with schizophrenia, Meyer and colleagues have shown that the prevalence of metabolic syndrome for olanzapine increased over 3 months from a baseline of 34.8% to 43.9%, but decreased for ziprasidone from 37.7% to 29.9%.15 Others have confirmed this notion by reporting significant differences in the cumulative incidence of metabolic syndrome between treatments, with a nearly 20% incidence of metabolic syndrome in the olanzapine group compared with approximately 13% incidence in the placebo group, and an 8% incidence in the aripiprazole group, which represents a 69% relative risk reduction for aripiprazole compared with olanzapine.16 The CATIE researchers also reported that despite variable effect sizes across subgroups, at 3 months olanzapine and quetiapine were associated with the largest mean increase in waist circumference (0.7 in for both), followed by risperidone (0.4 in). This is in comparison to no changes evidenced for ziprasidone (0.0 in) and a decrease in waist circumference for perphenazine (â&#x2C6;&#x2019;0.4 in). Olanzapine was also associated with significant changes in fasting triglycerides at 3 months (+21.5 mg/dL) compared with ziprasidone (â&#x2C6;&#x2019;32.1 mg/dL).15 Substantially greater weight gain with olanzapine (0.9 kg/month) than with quetiapine or risperidone (both 0.2 kg/month) was also reported. Perphenazine and ziprasidone were associated with losses of 0.1 kg/month.17 Similar to industry-sponsored studies that have a registration intent, CATIE most likely enrolled patients who had many years of previous drug exposure and, as such, their exposure might have underestimated the magnitude of drug effect on weight. Trials of drug-naive patients or patients with very little exposure have suggested much larger increases in weight with these drugs (Table 2, see print issue).

Why Do Atypical Antipsychotics Differ?

As previously suggested, some atypical antipsychotic medications seem to carry higher risks for metabolic syndrome than others. Researchers have attempted to determine which molecular binding sites are most closely linked with specific side effects, such as weight gain, glucose dysregulation, diabetes, and dyslipidemia, across a variety of antipsychotic agents. Despite a greater understanding of the biochemical effects of many of these medications in recent years, the pharmacologic mechanisms underlying their respective therapeutic properties and related side effects remain uncertain.

For example, in addition to dopamine D2 receptor

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antagonism, which is a characteristic feature of all atypical antipsychotic drugs, these agents also bind to a range of nondopaminergic targets, including serotonin, glutamate, histamine, alpha-adrenergic, and muscarinic receptors and their subtypes.18 Parsing molecular mechanisms associated with an effective antipsychotic agent from those associated with dyslipidemia and other components of metabolic syndrome has been challenging and generally not very clinically informative.

Despite this, it is apparent that metabolic consequences of atypical antipsychotic medications vary greatly with respect to receptor pharmacology, with mutual touch points suggesting common pathophysiologic mechanisms. For example, it has long been observed that the 2 drugs that appear to have the largest effect on body weight (olanzapine and clozapine) also have high affinity for 5-HT2C and histamine H1 receptors.19 Furthermore, it has been speculated that drugs whose actions work primarily on peripheral M3 muscarinic receptors and central 5-HT2C receptors seem to have an effect on diabetes that is independent of obesity.

Other receptors that may be implicated in synergistic effects include D2 receptor antagonistic enhancement of 5-HT2Câ&#x20AC;&#x201C;mediated effects on food intake, and disinhibition of prolactin control mechanisms, which influences glucose metabolism.

Downstream effects and mechanisms not shared by antipsychotic drugs are undoubtedly contributory, and many of the more reductionistic comparisons fail to take into account subtle distinctions in receptor-binding properties, such as partial agonism, inverse agonism, or synergistic effects across different processes in this association. In addition, the role of various metabolic syndrome biomarkersâ&#x20AC;&#x201D;such as leptin, ghrelin, and adiponectinâ&#x20AC;&#x201D;in providing a molecular bridge between antipsychotic medication use and heightened cardiovascular comorbidity needs to be more fully delineated.

Taking as many of the above factors into account as possible, Reynolds and Kirk assessed the relative affinities at relevant receptors for currently used antipsychotic drugs and provided substantive evidence that both olanzapine and clozapine are qualitatively more problematic than other drugs in both the severity of associated weight gain and the risk of glucose intolerance.19 They also reported that, compared with patients receiving antipsychotic monotherapy, patients receiving antipsychotic polytherapy seem to have higher rates of metabolic syndrome and lipid markers of insulin resistance.19 This is an important finding, because the use of multiple antipsychotic medications is very common in schizophrenia (in as much as 30%-40% of patients). However, Reynolds and Kirk noted that antipsychotic polytherapy was not independently associated with the prevalence of

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metabolic syndrome according to logistic regression but was instead dependent on demographic, clinical, and anthropometric risk factors such as higher BMI, older age, a diagnosis of bipolar disorder or schizophrenia, and cotreatment with a first-generation antipsychotic medication.19 Other researchers have confirmed that some association between polytherapy (polypharmacy) with antipsychotic agents and metabolic syndrome exists even after correcting for lifestyle differences.20

Patient Monitoring In 2004, the US Food and Drug Administration (FDA) required manufacturers of atypical antipsychotics to include a label warning about the risks of hyperglycemia and diabetes, and suggested regular clinical monitoring of weight, symptoms of hyperglycemia, and glucose. Manufacturers of atypical antipsychotic medications were required to send letters to healthcare professionals informing them of these warnings and advising them of the need for glucose testing in patients receiving atypical antipsychotic medications who also had a diagnosis of diabetes, risk factors for diabetes, or symptoms of hyperglycemia.

In advance of this labeling, the American Diabetes Association (ADA), in conjunction with representatives of the American Psychiatric Association (APA), American Association of Clinical Endocrinologists, and North American Association for the Study of Obesity, held a meeting in November 2003 to review the available data on metabolic effects of atypical antipsychotic medications and solicit input from industry experts in the fields of psychiatry, obesity, and diabetes, as well as from the FDA. This mix of therapeutic expertise reflects the multidisciplinary approach that is essential for both detection and treatment of metabolic syndrome in this patient population.

The consensus recommendations for metabolic monitoring of patients receiving atypical antipsychotic agents have been widely published. These include assessments at baseline, 4 weeks, 8 weeks, 12 weeks, quarterly, annually, and every 5 years for factors such as personal/ family history, weight (BMI), waist circumference, BP, FPG, and fasting lipid profile.21 Specifically, this guidance recommends testing of FPG levels (at baseline, 12 weeks, then annually) and a fasting lipid profile (at baseline, 12 weeks, then every 5 years if normal; Table 3, see print issue). These recommendations embody a basic principle about the healthcare of patients with chronic mental illness: that this group often receives inadequate healthcare monitoring outside of the psychiatric clinical setting.22 Despite some discordant definitions, all guidelines support a common course of action for the evaluation of

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patients when initiating and maintaining therapy with antipsychotic drugs that includes recognition of both nonmodifiable and modifiable risk factors. Nonmodifiable risk factors include increasing age, sex (with increased rates of obesity, diabetes, and metabolic syndrome in treated female patients); personal and family history of obesity, diabetes, heart disease; and ethnicity (with increased rates of diabetes, metabolic syndrome, and coronary heart disease in patients of non-European descent). Modifiable risk factors include obesity, visceral obesity, smoking, physical inactivity, and dietary habits.

The impact of smoking, ubiquitous in patients with schizophrenia, is particularly notable on major outcomes, such as cancer, pulmonary disease, and CVD.23 Despite these explicit requirements, little data are available to suggest uniform clinician adherence to monitoring recommendations with wide variability noted among medical specialties, institutions, and regions. In some clinical settings, for example, less than one third of patients treated with atypical antipsychotic medications undergo any blood glucose or lipid testing. In addition, promulgation of guidance does not necessarily result in a change in surveillance.

Morrato and colleagues examined a 3-state population of Medicaid recipients and found that diabetes and dyslipidemia screening among patients receiving atypical antipsychotic medications was low and did not increase after the FDA warnings or recommendations from the ADA and APA.24 They compared surveillance activity before and after the FDA warning in a group of 109,451 patients receiving atypical antipsychotic agents and a control group of 203,527 patients who began taking albuterol but who did not receive antipsychotic medication. Baseline glucose and lipid testing rates for atypical antipsychotic–treated patients were low at 27% and 10%, respectively. After the FDA warning, glucose testing and lipid testing rates only increased by a marginal 1.7%.24 Strikingly, testing rates and trends among atypical antipsychotic–treated patients were no different from those in the albuterol control group. Testing rates were moderated by several variables, including location, ethnicity, sex, and type of antipsychotic medication, emphasizing a consensus that efforts used to enhance surveillance must be tailored to the environment where the care is actually delivered.

Reasons for lack of adherence to monitoring that have been described are related to factors such as availability of clinic resources, lack of awareness of the enhanced liability of metabolic syndrome, inconsistent dissemination of guidance in psychiatry, and possibly the nature and complexity of the guidance itself. For example, Cohn and colleagues have suggested that top-down guidance, such as that currently in use, may be better

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served by a combined approach that uses both top-down and bottom-up strategies, utilizing representatives of both community and nongovernmental organizations in addition to academic healthcare professionals.25 The nature of the recommended process for surveillance itself represents a complexity that cannot be approached in a real-world monitoring setting where available equipment, patient cooperation, and time constraints limit application of the full montage of recommended tests. A default simple measure of waist circumference as a reflection of central obesity may be informative in the absence of the full spectrum of laboratory measures, although it too has been inconsistently applied.26 Not all research on adherence to guidance has been disconcerting. For example, Barnett and colleagues reported that patients taking atypical antipsychotic medications were more likely than those patients taking first-generation drugs to undergo glucose testing (odds ratio [OR], 1.38) and lipid testing (OR, 1.43).27 Patients taking atypical antipsychotic agents were also more likely to receive both glucose and lipid testing in the 6 months after initiation of antipsychotic treatment, particularly if they were tested during the 6 months before initiation of antipsychotic medication.

Individual second-generation antipsychotics—aripiprazole, olanzapine, quetiapine, risperidone, and ziprasidone—were also reportedly associated with higher rates of testing.

In addition, in the year after the FDA warnings, 60% to 80% of psychiatrists reported monitoring glucose and lipid levels at regular intervals.28 A national survey of community mental health centers also indicated that two thirds of community mental health centers reported having protocols or procedures to screen for common medical problems, such as diabetes and dyslipidemia.29 Obviously, this finding belies the objective data from Morrato and colleagues on the US Medicaid databases previously cited.24 Whatever the actual rates, it is clear that increased monitoring does not appear to occur universally in the population with schizophrenia receiving atypical antipsychotics and may be strongly influenced by setting (eg, urban mental healthcare centers and tertiary care hospitals vs private clinics) and geographic regions where these data have been derived (eg, United States, United Kingdom, Japan, India). Therefore, more research is needed to better understand these factors before improvements can be made in diabetes and dyslipidemia screening for this at-risk population.

Responsibility for Surveillance One reason for inconsistent monitoring is that opin-

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ion is divided on whose responsibility it is to undertake monitoring. Some suggest that psychiatrists who prescribe the medication and see the patients more frequently are the most appropriate to assume monitoring responsibilities, because patients with schizophrenia are less likely to have access to a general practitioner who might be able to integrate all healthcare interventions.

Other researchers have taken the view that there needs to be a much more coordinated approach between primary and secondary care. There is also some general agreement that patients should be encouraged to selfmonitor, especially for the signs and symptoms of emergent diabetes or diabetic ketoacidosis, particularly during the first few months of antipsychotic treatment (when risk is the highest).

However, self-monitoring may not be achievable in a large segment of the population with schizophrenia, because the illness itself is characterized by diminished cognitive function, poor insight, denial of illness, and impaired ability to recognize and verbalize physical complaints. All of these factors lead to an increased responsibility for intervention on the part of healthcare professionals and caregivers. Cohn and colleagues have argued that monitoring, but not necessarily medical treatment of metabolic syndrome, falls within the scope of psychiatric practice and should include screening for metabolic disturbance as well as tracking the effects of antipsychotic treatment, given that the primary (and perhaps only) point of contact with the healthcare system is through the psychiatric treatment team.25 Hasnain and Vieweg also opined that effective communication between the primary care physician and the psychiatrist is particularly important for the mentally ill, because of the patientsâ&#x20AC;&#x2122; impaired capacity to care for themselves.9 The authors agreed that monitoring for metabolic side effects is primarily the responsibility of the physician prescribing antipsychotic medication. In most cases, that would be the psychiatrist, with a primary care physician (if involved) providing additional vigilance. Should the psychiatrist not have the expertise to manage any detected abnormalities, the primary care physician would most likely take over both monitoring and management. In practice, local resources and service arrangements may help determine who is most appropriately placed to monitor patients with clear communication between clinicians being paramount.

What Should Be Monitored?

The decision as to who has primary responsibility for monitoring is dependent on parameters being monitored, and numerous studies have suggested â&#x2030;Ľ1 test as being the most beneficial. Given guidance and the importance of directly monitoring glucose, several

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researchers have attempted to reduce both time and costs associated with glucose monitoring specifically. For example, a much shorter duration of fasting for glucose intolerance and metabolic syndrome has been suggested

by McLellan and colleagues, who reported that the positive predicted value of elevated capillary glucose at 4 hours for predicting elevated levels obtained on repeat testing after an 8-hour fast was 57%.30 In addition, a novel dynamic insulin sensitivity and secretion test (DISST) used for measuring insulin sensitivity has been developed and can be performed in approximately 30 minutes. The DISST is a low-cost, low-intensity alternative to the glucose clamp, with the added benefits of measuring beta-cell function and the ability to differentiate individual variations in pathophysiology.31 In addition to these direct laboratory-based assessments, Stahl recommended an integrated clinical approach including a directive to (1) weigh patients and track BMI at each visit; (2) determine the presence of risk factors at baseline and at intervals after treatment initiation; (3) obtain a baseline fasting glucose level and lipid profile for psychiatric patients who have a BMI â&#x2030;Ľ27 kg/m2, then track glucose and lipid levels at regular intervals, especially if further weight gain occurs; and (4) monitor glucose levels frequently, including shortly after beginning a new antipsychotic agent and when treating a patient with diabetes.32 However, studies have found that even simple measurements of waist circumference are rarely conducted and that overall monitoring for metabolic adverse events of antipsychotic medication (eg, hypertension and hyperglycemia) is poor.26,33,34 In a more rigorous application of monitoring, Straker and colleagues examined a consecutive group of 100 psychiatric inpatients treated with at least 1 atypical antipsychotic medication.35 They measured BP and waist circumference at the level of the umbilicus, as well as FPG and lipid levels. They reported that 29% of patients fulfilled criteria for metabolic syndrome and the presence of metabolic syndrome was associated with older age, higher BMI, and higher values for each individual criterion of metabolic syndrome, but not with the specific diagnoses or antipsychotic treatment regimens.

Among the 5 criteria used to predict metabolic syndrome, abdominal obesity had the highest sensitivity, correctly identifying 92.0% patients. Elevated FPG served as the most specific criterion, with normal values appropriately categorizing 95.2% of patients without metabolic syndrome. When abdominal obesity and/or FPG were combined, 100% of patients with metabolic syndrome were correctly identified, whereas combining abdominal obesity and/or elevated BP resulted in the correct identification of 96.2% of patients.

Others researchers, such as Lin and colleagues, have

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taken these simple combinations of risk factors to the next level by using artificial neural network (ANN) and multiple logistic regression techniques to identify metabolic syndrome.36 This approach may be applicable in healthcare settings characterized by access to a common data set and predictive modeling capabilities. In a group of 383 patients with schizophrenia and schizoaffective disorder, these researchers suggested that waist circumference and diastolic BP were the most predictive variables, with 93% of metabolic syndrome cases and 87% of nonmetabolic syndrome successfully identified by the ANN model, and approximately 86% of metabolic syndrome and 84% of nonmetabolic syndrome successfully predicted by a logistic regression model.

This finding implies that most patients with metabolic syndrome treated with an atypical antipsychotic could be successfully identified by model prediction using only a few easily and immediately available clinical variables (eg, waist circumference, diastolic BP, BMI, and female sex), contingent on choice of predictive modeling adopted. Currently, physicians rely mostly on a univariate examination of laboratory data when diagnosing metabolic syndrome. However, with data supporting both high sensitivity and negative predictive values, multivariate algorithmic models show promise for assisting physicians in the clinical screening of metabolic syndrome.

Healthcare Implications Schizophrenia is a chronic and costly illness that requires life-long treatment with antipsychotic medications that have a wide range of associated side effects.

Given the diversity of stakeholders involved in the provision of healthcare, the impact of metabolic syndrome associated with atypical antipsychotics can vary appreciably. Costs related to schizophrenia medication treatment and supportive care have often been viewed as being outside the auspices of managed care, given the preponderance of patients who receive treatment with sole advocacy and aegis by state and government agencies, such as Medicaid. However, regardless of the payer involvement, metabolic syndrome differences among various antipsychotic agents (and their effect on efficacy, safety, tolerability, and adherence) have substantial cost implications for society.

Several studies have assessed the role of various antipsychotic medications in healthcare costs, and surprisingly, much of the available data do not support drastic cost differences between schizophrenic patients with and without metabolic syndrome at least over short time frames, with very little impact of monitoring cost overall. For example, Vera-Llonch and colleagues used a Markov model to examine outcomes and costs of care

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in patients with chronic schizophrenia or schizoaffective disorders receiving risperidone or olanzapine over a 1-year period.37 They examined incidence of relapse and selected side effects, including extrapyramidal symptoms, prolactin-related disorders, and diabetes, and change in body weight. The expected incidence of diabetes mellitus, although low, was slightly higher for olanzapine. Furthermore, approximately 25% and 4% of patients treated with olanzapine and risperidone, respectively, were projected to experience an increase in body weight â&#x2030;Ľ7%. The expected mean total costs of care per month of therapy were $2163 for risperidone and $2316 for olanzapine.

Overall, the costs associated with antipsychotic therapy, diagnosis and treatment of side effects, and discontinuation and switching of antipsychotic therapy were higher among patients treated with olanzapine.

Compared with risperidone, treatment with olanzapine was associated with greater increases in body weight, higher rates of therapy discontinuation, and resulting higher costs of medical care services.

There is little justification from a purely economic point of view for more broad-based surveillance after brief durations of therapy. However, it is difficult to determine if relatively small differences in costs between medication groups, which are commonly noted within the first year of treatment initiation eg, would be amplified and sustained over longer periods of time (5-10 years). There is some notion that adverse events associated with metabolic risk increase as patients mature. Although indirect costs associated with loss of workplace productivity may not be as substantive in a population that is typically unemployed or employed only in a supported environment, direct medical costs associated with macrovascular complications and hyperglycemic episodes can be considerable over the course of many years. Also, large cost drivers, such as stroke and heart disease, may not develop until much further into the metabolic process. Given the relatively low cost of monitoring with very little if any safety implications resulting from the monitoring procedures, it seems prudent to adopt policies that would enhance surveillance in the schizophrenia patient population to prevent morbidity and mortality.

In terms of impacting cost, point of care (POC) testing, or diagnostic testing/therapeutic monitoring carried out at or near the site of the patient, may be beneficial. Adoption of this procedure has been demonstrated to reduce labor costs and manual procedure steps in other settings and eliminates the time lag associated with laboratory testing, leading to quicker therapeutic action and improved outcomes. This approach is not new to medicine, with more than

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90,000 medical offices performing POC testing in the United States, including tests to determine blood glucose, pregnancy, strep throat, substances of abuse, and prothrombin time.38 As the volume of POC testing increases, costs relative to manual procedures decline. In the setting of a systematic treatment care team, POC testing has been shown to be effective in assessing for metabolic syndrome by merely checking for the combination of elevated abdominal obesity and FPG levels, thus providing a practical method for identifying metabolic risk in patients taking atypical antipsychotic medications.39

The treatment of schizophrenia involves a delicate balance in terms of risks and benefits, because failing to treat as a result of risk for or complications from metabolic syndrome may place the patient at a higher risk for more serious problems, or even suicide.

In addition, the availability of POC testing methods for blood glucose levels creates new opportunities for behavioral healthcare providers, because instant glucose meters and strips are Clinical Laboratory Improvement Amendments–waived by the FDA, and thus can be used in office environments. The need for a shift in reimbursement policy to encourage POC testing in the behavioral health arena would represent a unique challenge for payers that have historically favored laboratory-driven versus practitioner-driven tests. It also is possible that this increase in accessibility and shift in policy regarding reimbursement could decrease the reluctance of some practitioners to both prescribe and monitor the effects of antipsychotic medications in both schizophrenia and other patient indications, but this remains to be tested.

Conclusions The treatment of schizophrenia involves a delicate balance in terms of risks and benefits, because failing to treat as a result of risk for or complications from metabolic syndrome may place the patient at a higher risk for more serious problems, or even suicide. Although atypical antipsychotic medications differ in the prevalence of metabolic syndrome, the molecular mechanisms subtending their effects are not well understood, and the prospects of “designing out” the propensity for metabolic syndrome with innovative antipsychotic medications remain uncertain for the immediate future.

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Surveillance systems are particularly noteworthy, because increased monitoring of simple clinical and laboratory measures of metabolic syndrome may help decrease important adverse events in multiple organ systems and ultimately improve patients’ quality of life.

Activities to enhance surveillance include the recognition that each patient touches a system of care in which coordinated services are required from multiple healthcare providers in an interdependent manner. POC systems and predictive modeling now in development have the potential to expand access to monitoring and increase compliance with monitoring guidance. ■ Author Disclosure Statement Dr Riordan, Dr Antonini, and Dr Murphy are salaried employees of Worldwide Clinical Trials, an international, full-service, contract research organization that specializes in clinical research activities in support of the pharmaceutical industry. Relationships exist with multiple (>100) pharmaceutical companies as part of their primary business activity.

References 1. World Health Organization. Preventing chronic diseases: a vital investment. 2005. www.who.int/chp/chronic_disease_report/full_report.pdf. Accessed August 15, 2011.

2. Brown S. Excess mortality of schizophrenia. A meta-analysis. Br J Psychiatry. 1997; 171:502-508.

3. Newcomer JW. Second-generation (atypical) antipsychotics and metabolic effects: a comprehensive literature review. CNS Drugs. 2005;19(suppl 1):1-93.

4. Saddichha S, Manjunatha N, Ameen S, Akhtar S. Metabolic syndrome in first episode schizophrenia—a randomized double-blind controlled, short-term prospective study. Schizophr Res. 2008;101:266-272.

5. De Hert M, Dobbelaere M, Sheridan EM, et al. Metabolic and endocrine adverse effects of second-generation antipsychotics in children and adolescents: a systematic review of randomized, placebo controlled trials and guidelines for clinical practice.

Eur Psychiatry. 2011;26:144-158.

6. International Diabetes Federation. The IDF consensus worldwide definition of the metabolic syndrome. International Diabetes Federation (IDF), 2006. www.idf.org/ webdata/docs/IDF_Meta_def_final.pdf. Accessed August 15, 2011.

7. Coccurello R, Moles A. Potential mechanisms of atypical antipsychotic-induced metabolic derangement: clues for understanding obesity and novel drug design.

Pharmacol Ther. 2010;127:210-251.

8. Haupt DW. Differential metabolic effects of antipsychotic treatments. Eur Neuropsychopharmacol. 2006;16(suppl 3):S149-S155.

9. Hasnain MR, Vieweg WV. Acute effects of newer antipsychotic drugs on glucose metabolism. Am J Med. 2008;121:e17; author reply e19.

10. Prussian KH, Barksdale-Brown D, Dieckmann J. Racial and ethnic differences in the presentation of metabolic syndrome. J Nurse Pract. 2007;3:229-239.

11. Correll CU, Frederickson AM, Kane JM, Manu P. Does antipsychotic polypharmacy increase the risk for metabolic syndrome? Schizophr Res. 2007;89:91-100.

12. de Leon J, Susce MT, Johnson M, et al. A clinical study of the association of antipsychotics with hyperlipidemia. Schizophr Res. 2007;92:95-102.

13. Mulder H, Cohen D, Scheffer H, et al. HTR2C gene polymorphisms and the metabolic syndrome in patients with schizophrenia: a replication study. J Clin Psychopharmacol. 2009;29:16-20.

14. Meyer JM. A retrospective comparison of weight, lipid, and glucose changes between risperidone- and olanzapine-treated inpatients: metabolic outcomes after 1 year. J Clin Psychiatry. 2002;63:425-433.

15. Meyer JM, Davis VG, Goff DC, et al. Change in metabolic syndrome parameters with antipsychotic treatment in the CATIE Schizophrenia Trial: prospective data from phase 1. Schizophr Res. 2008;101:273-286.

16. L’Italien GJ. Pharmacoeconomic impact of antipsychotic induced metabolic events. Prev Med Manag Care. 2003;3(suppl 2):S38-S42.

17. Lieberman JA, Stroup TS, McEvoy JP, et al. Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. N Engl J Med. 2005;353:1209-1223. Erratum in N Engl J Med. 2010;363:1092-1093.

18. Nasrallah HA. Atypical antipsychotic-induced metabolic side effects: insights from receptor-binding profiles. Mol Psychiatry. 2008;13:27-35.

19. Reynolds GP, Kirk SL. Metabolic side effects of antipsychotic drug treatment— pharmacological mechanisms. Pharmacol Ther. 2010;125:169-179.

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20. Misawa F, Shimizu K, Fujii Y, et al. Is antipsychotic polypharmacy associated with metabolic syndrome even after adjustment for lifestyle effects: a cross-sectional study.

BMC Psychiatry. 2011;11:118.

21. American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care. 2004;27:596-601.

22. Jin H, Meyer JM, Jeste DV. Atypical antipsychotics and glucose dysregulation: a systematic review. Schizophr Res. 2004;71:195-212.

23. Prochaska JJ. Smoking and mental illnessâ&#x20AC;&#x201D;breaking the link. N Engl J Med. 2011; 365:196-198.

24. Morrato EH, Libby AM, Orton HD, et al. Frequency of provider contact after FDA advisory on risk of pediatric suicidality with SSRIs. Am J Psychiatry. 2008;165:42-50.

25. Cohn TA, Remington G, Zipursky RB, et al. Insulin resistance and adiponectin levels in drug-free patients with schizophrenia: a preliminary report. Can J Psychiatry.

2006;51:382-386.

26. Waterreus AJ, Laugharne JD. Screening for the metabolic syndrome in patients receiving antipsychotic treatment: a proposed algorithm. Med J Aust. 2009;190:185-189.

27. Barnett M, VonMuenster S, Wehring H, et al. Assessment of monitoring for glucose and lipid dysregulation in adult Medi-Cal patients newly started on antipsychotics. Ann Clin Psychiatry. 2010;22:9-18.

28. Suppes T, McElroy SL, Hirschfeld R. Awareness of metabolic concerns and perceived impact of pharmacotherapy in patients with bipolar disorder: a survey of 500 US psychiatrists. Psychopharmacol Bull. 2007;40:22-37.

29. Druss BG, Marcus SC, Campbell J, et al. Medical services for clients in community mental health centers: results from a national survey. Psychiatr Serv. 2008;59:917-920.

30. McLellan RK, Comi RJ, Mackenzie TA, et al. The usefulness and cost of a shorter duration of fasting in workplace screening for glucose intolerance and metabolic syndrome. Diabetes Res Clin Pract. 2009;84:e6-e8.

31. Goodman A. Diabetes screening of high-risk people is cost-effective. Am Health Drug Benefits. 2010;3 suppl:S1-S12.

32. Stahl S. The metabolic syndrome: psychopharmacologists should weigh the evidence for weighing the patient. J Clin Psychiatry. 2002;63:1094-1095.

33. Newcomer JW, Nasrallah HA, Loebel AD. The atypical antipsychotic therapy and metabolic issues national survey: practice patterns and knowledge of psychiatrists. J Clin Psychopharmacol. 2004;24(5 suppl 1):S1-S6.

34. Mackin P, Bishop DR, Watkinson HM. A prospective study of monitoring practices for metabolic disease in antipsychotic-treated community psychiatric patients.

BMC Psychiatry. 2007;7:28.

35. Straker D, Correll CU, Kramer-Ginsberg E, et al. Cost-effective screening for the metabolic syndrome in patients treated with second-generation antipsychotic medications. Am J Psychiatry. 2005;162:1217-1221.

36. Lin CC, Bai YM, Chen JY, et al. Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models. J Clin Psychiatry. 2010;71:225-234.

37. Vera-Llonch M, Delea TE, Richardson E, et al. Outcomes and costs of risperidone versus olanzapine in patients with chronic schizophrenia or schizoaffective disorders: a Markov model. Value Health. 2004;7:569-584.

38. Glazer WM. Point-of-care tests in behavioral health. Behav Healthc. 2006;26:37-39.

39. Schneiderhan ME, Batscha CL, Rosen C. Assessment of a point-of-care metabolic risk screening program in outpatients receiving antipsychotic agents.

Pharmacotherapy. 2009;29:975-987.

STAKEHOLDER PERSPECTIVE The Complexities of Treating Mental Illness MEDICAL/PHARMACY DIRECTORS: Here is what we knowâ&#x20AC;&#x201D;atypical antipsychotic medications are the standard of care for pharmacologic treatment of schizophrenia. We also know that these medications can significantly increase the risk for cardiovascular disease because of the metabolic syndrome association.

What we seem to have forgotten, or have opted to ignore, is that metabolic syndrome can be screened and effectively prevented or treated when diagnosed.

The article by Riordan and colleagues in this issue of American Health & Drug Benefits provides an excellent review of the literature regarding atypical antipsychotics and the mechanism of their link to metabolic syndrome. Other review articles regarding this issue have focused on treatment options for metabolic syndrome,1 but the present article by Riordan and colleagues provides important information on techniques to screen for metabolic syndrome, such as point of care testing focusing on abdominal obesity and fasting blood

glucose, as well as the coordination of care between primary care and specialty care providers.

The authors also provide some insight into the complexities of providing appropriate care to patients with serious mental illness. Whether you have directly provided care to patients with serious mental illness or not, it is apparent how difficult this can be. To a certain extent, this difficulty is a microcosm of some of the general challenges we have in providing appropriate care to any patient in this country.

One of the common challenges is the coordination of care between a primary care provider and a specialty care provider. Once a patient has been seen by a psychiatrist, or an oncologist for that matter, and is prescribed therapy for a new diagnosis that can increase the risk for diabetes, is it the responsibility of the specialist or of the primary care physician to screen and treat for diabetes? The ideal situation would involve an open dialogue between both providers to ensure that Continued

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STAKEHOLDER PERSPECTIVE (Continued) the patient is receiving appropriate care, but this does not happen as often as it should.

Another challenge is ensuring adherence to prescribed pharmacologic therapy. This is a challenge encountered in the general population for several reasons (eg, intolerance to therapy, inability to afford medications, illiteracy) and is very common in the treatment of patients with schizophrenia. Ideally, patients with schizophrenia will have medications available that effectively control their illness with minimal side effects. The use of depot formulations should also be considered.

The authors also provide some insight into the costs associated with metabolic syndrome caused by atypical antipsychotics, and these costs are very significant. Indeed, although the focus of the article is on schizophrenia, atypical antipsychotics are often being used for the treatment of depression, obsessivecompulsive disorder, attention-deficit/hyperactivity disorder, and other conditions. In addition, with changes in healthcare coverage taking place on a

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national level as a result of the healthcare reform, more patient-specific illnesses will have access to treatment with atypical antipsychotics. This will all add to a difficult situation we are facing today in the use of atypical antipsychotics and the incidence of metabolic syndrome.

ALL STAKEHOLDERS: As healthcare professionals, it is important for all of us to read the current article by Riordan and colleagues in American Health & Drug Benefitsâ&#x20AC;&#x201D;to get a better understanding of the challenges in screening and treating metabolic syndrome associated with atypical antipsychotics, and to implement appropriate solutions to these challenges.

In the absence of appropriate solutions, we will be transitioning from complexities to chaos.

1. Pramyothin P, Khaodhiar L. Metabolic syndrome with the atypical antipsychotics. Curr Opin Endocrinol Diabetes Obes. 2010;17:460-466.

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Atheer A. Kaddis, PharmD Vice President, Managed Markets Diplomat Specialty Pharmacy

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REVIEW ARTICLE

Current Therapies and Emerging Drugs in the Pipeline for Type 2 Diabetes Quang T. Nguyen, DO; Karmella T. Thomas, BS, RD; Katie B. Lyons, MS II; Loida D. Nguyen, PharmD, BCBS; Raymond A. Plodkowski, MD Background: Diabetes is a global epidemic that affects 347 million people worldwide and 25.8 million adults in the United States. In 2007, the total estimated cost associated with diabetes in the United States in 2007 was $174 billion. In 2009, $16.9 billion was spent on drugs for diabetes. The global sales of diabetes pharmaceuticals totaled $35 billion in 2010, and these are expected to rise to $48 billion by 2015. Despite such considerable expenditures, in 2000 only 36% of patients with type 2 diabetes in the United States achieved glycemic control, defined as hemoglobin A1c <7%.

Objective: To review some of the most important drug classes currently in development for the treatment of type 2 diabetes.

Discussion: Despite the 13 classes of antidiabetes medications currently approved by the US Food and Drug Administration (FDA) for the treatment of type 2 diabetes, the majority of patients with this chronic disease do not achieve appropriate glycemic control with these medications. Many new drug classes currently in development for type 2 diabetes appear promising in early stages of development, and some of them represent novel approaches to treatment, with new mechanisms of action and a low potential for hypoglycemia. Among these promising pharmacotherapies are agents that target the kidney, liver, and pancreas as a significant focus of treatment in type 2 diabetes. These investigational agents may potentially offer new approaches to controlling glucose levels and improve outcomes in patients with diabetes. This article focuses on several new classes, including the sodium-glucose cotransporter-2 inhibitors (which are furthest along in development); 11beta-hydroxysteroid dehydrogenase (some of which are now in phase 2 trials); glycogen phosphorylase inhibitors; glucokinase activators; G protein–coupled receptor 119 agonists; protein tyrosine phosphatase 1B inhibitors; and glucagon-receptor antagonists.

Conclusion: Despite the abundance of FDA-approved therapeutic options for type 2 diabetes, the majority of American patients with diabetes are not achieving appropriate glycemic control. The development of new options with new mechanisms of action may potentially help improve outcomes and reduce the clinical and cost burden of this condition.

D

iabetes is a chronic, progressive disease that affects approximately 347 million people worldwide.1 In the United States, 25.8 million Americans have diabetes, and another 79 million US adults aged ≥20 years are considered to have prediabetes.2 Diabetes is the leading cause of kidney failure, nontrau-

Quang T. Nguyen

Stakeholder Perspective, page 311

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matic lower-limb amputations, and new cases of blindness among adults in the United States. It is a major cause of heart disease and stroke and is the seventh leading cause of death among US adults.2 The total estimated cost for diabetes in the United States in 2007 was $174 billion,2 and between 2007 and

Dr Quang Nguyen, Endocrinology Department, Carson Tahoe Physician Clinics–Carson City, Assistant Clinical Professor of Endocrinology and Internal Medicine, University of Nevada School of Medicine, Reno, and Adjunct Associate Professor of Endocrinology and Internal Medicine, Touro University Nevada, Henderson, College of Osteopathic Medicine; Ms Thomas is Clinical Registered Dietitian, Carson Tahoe Physician Clinics and University of Nevada, Reno, Department of Endocrinology, Nutrition and Metabolism; Ms Lyons is a medical student, University of Nevada School of Medicine, Reno; Dr Loida Nguyen is Clinical Pharmacist, Sierra Nevada Healthcare System, Veterans Affairs Medical Center, Reno; and Dr Plodkowski is Chief of Endocrinology, University of Nevada, and Veterans Affairs Medical Center, Reno.

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KEY POINTS ➤

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Approximately 25.8 million adult Americans have diabetes. In 2007, diabetes cost the United States an estimated $174 billion, and in 2009, $16.9 billion was spent on antidiabetes medications.

Nevertheless, the majority of American patients with diabetes do not achieve glycemic control with the currently available pharmacotherapies.

Several novel and promising medications are currently in development, targeting the kidney, liver, and pancreas in the treatment of type 2 diabetes.

Many of these investigational agents involve new mechanisms of action that offer new therapeutic targets and may help improve glucose control in patients with diabetes.

The new drug classes in development include the sodium-glucose cotransporter-2 inhibitors (which are furthest along in development); the 11betahydroxysteroid dehydrogenase; glycogen phosphorylase inhibitors; glucokinase activators; G protein–coupled receptor 119 agonists; protein tyrosine phosphatase 1B inhibitors; glucagonreceptor antagonists.

Several of these new classes are associated with low potential for hypoglycemia, representing a potentially new approach to diabetes drug therapy.

The development of new options with new mechanisms of action may potentially help improve patient outcomes and reduce the clinical and cost burden of this chronic disease.

2009, the estimated cost attributable to pharmacologic intervention in the treatment of diabetes increased from $12.5 billion to $16.9 billion.3-5 Global sales for diabetes medications totaled $35 billion in 2010 and could rise to $48 billion by 2015, according to the drug research company IMS Health.6,7 In 2009, $1.1 billion was spent on diabetes research by the National Institutes of Health.8 Despite these staggering costs, currently there are still no proved strategies to prevent this disease or its serious complications.

According to the 1999-2000 National Health and Nutrition Examination Survey, only 36% of patients with type 2 diabetes achieve glycemic control—defined as hemoglobin (Hb) A1c <7%—with currently available therapies.9 Lifestyle modification remains the most important and effective way to treat diabetes; however, the majority of patients with type 2 diabetes are unable to maintain such a rigid lifestyle regimen. For most patients with type 2 diabetes, pharmacologic intervention will therefore be needed to maintain glycemic control.2

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Tables 1 and 2 list the 13 classes of medication currently approved by the US Food and Drug Administration (FDA) for the treatment of type 2 diabetes. Despite this abundance of pharmacotherapies, new medications with different mechanisms of action or new approaches to therapy are needed to improve patient outcomes and reduce the clinical and cost burden of this serious condition.

Indeed, the number of diabetes medications for type 2 diabetes is expected to grow in the next few years, considering the many promising investigational therapeutic options currently in development that may gain FDA approval in the future. This article reviews some of the therapies that are currently being tested and may soon become new options for the treatment of type 2 diabetes (Table 3).

Sodium-Glucose Cotransporter-2 Inhibitors The sodium-glucose cotransporter (SGLT)-2 inhibitors are a new investigational drug class for the treatment of type 2 diabetes. These agents work at the kidney through insulin-independent mechanisms and should, therefore, theoretically reduce the risk for weight gain that often plagues some of the current antidiabetes drugs.

The kidney contributes to glucose balance by: • Producing glucose through gluconeogenesis10 • Utilizing glucose in the renal medulla10 • Reabsorbing up to 100% of the filtered glucose to maintain the normal circulating glucose pool.11 Two sodium-dependent glucose transporters—SGLT1 and SGLT2—have been identified as the major transporters of glucose in humans.12,13 SGLT2 is expressed almost exclusively in the S1 segment of the proximal tubule and accounts for >90% of renal glucose reabsorption. SGLT1 is expressed in the heart, gastrointestinal tract, skeletal muscle, liver, and lung, and in the S3 segment of the proximal tubule, where it accounts for only <10% of filtered glucose reabsorption.14 SGLT2 is therefore the major transporter responsible for renal glucose reabsorption and is a useful therapeutic target for the treatment of diabetes.

Selective inhibition of this transporter will decrease the reabsorption of filtered glucose, lower plasma glucose concentration, and improve glycemic control. Few studies have indicated that the expression of SGLT2 is up-regulated in diabetes,15,16 a finding that emphasizes the importance of blocking this pathway to control or decrease plasma glucose. Several SGLT2 inhibitors have been developed and are in various phases of clinical trials.17 The most advanced agent in this class is dapagliflozin, which has been tested in phase 3 clinical trials in patients with type 2 diabetes as monotherapy,18 with metformin19 or with glimepiride,20 or in combination

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Colesevelam (Welchol)

Sitagliptin (Januvia) Saxagliptin (Onglyza) Linagliptin (Tradjenta)

Bile acid sequestrant

DPP-4 inhibitors

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Pioglitazone (Actos) Rosiglitazone (Avandia)

Thiazolidinediones

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Weight gain

Weight gain

Edema

Hypoglycemia

Hypoglycemia

Weight gain

Black box warning: These agents can cause or exacerbate CHF Contraindicated in patients with NYHA class III or IV heart failure

Use of these agents has declined in response to adverse effects and unpredictable results

Taken with meals to control rapid onset

Acute pancreatitis has been reported during postmarketing experience Injectable drug

Taken with meals Avoid use in patients with renal or hepatic impairment or with CHF, because of increased risk for lactic acidosis

Precautions/Comments Titrate slowly to minimize gastrointestinal effects Black box warning: Coadministration with insulin may induce severe hypoglycemia Injectable drug

Lacy CF, et al, eds. Drug Information Handbook. 18th ed. Hudson, OH: Lexi-Comp; 2009-2010.

Nathan DM, et al. Management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy. Diabetes Care. 2006;29:1963-1972.

CHF indicates congestive heart failure; DPP, dipeptidyl peptidase; HbA1c, glycated hemoglobin; NYHA, New York Heart Association.

b

a

1-2

Stimulate insulin secretion from the pancreas

Glimepiride (Amaryl) Glipizide (Glucotrol) Glyburide (Micronase, Diabeta, Glynase)

Second-generation sulfonylureas

0.5-1.4

1-2

Chlorpropamide (Diabinese) Stimulate insulin secretion Tolazamide (Tolinase) from the pancreas Tolbutamide (Orinase)

First-generation sulfonylureas

Hypoglycemia

Hypogylcemia

Weight gain

Up to 3.5

Nausea, vomiting, diarrhea

Nausea, vomiting dizziness, headache, diarrhea

Not clinically significant

Constipation, dyspepsia, nausea

Nausea, vomiting, diarrhea, flatulence

Adverse effectsa Flatulence, diarrhea, abdominal pain Nausea, vomiting

Weight gain

Weight loss

Weight neutral

Weight neutral

Weight neutral

Weight neutral

Effect on weight Weight neutral Weight loss

0.5-1

0.5-0.7

0.5-0.8

0.5

1-2

1-1.5

Stimulate insulin secretion, slows gastric emptying, suppresses glucagon release, induces satiety Exogenous insulin

Mechanism of action for diabetes control unknown

Decrease hepatic glucose output Increase peripheral glucose uptake Binds to intestinal bile acids Mechanism of action for diabetes control unknown Slow inactivation of incretin hormones

HbA1c Mechanism of actiona reduction, %b Delay complex carbohydrate 0.5-0.8 absorption Acts in conjunction with 0.5-1 insulin to prolong gastric emptying, reduce postprandial glucose secretion, promote appetite suppression

Stimulate insulin secretion from the pancreas

Incretin mimetics

Exanetide (Byetta) Liraglutide (Victoza) Insulin preparations: Refer to Table 2 rapid-, short-, intermediate-, long-acting, premixed Nateglinide (Starlix) Nonsulfonylurea Repaglinide (Prandin) secretagogues

Bromocriptine (Parlodel)

Metformin (Glucophage)

Biguanide

Dopamine agonist

Drug (brand) Acarbose (Precose) Miglitol (Glyset) Pramlintide (Symlin)

Class Alpha-glucosidase inhibitors Amylin analog

Table 1 FDA-Approved Antidiabetic Agents for the Treatment of Type 2 Diabetes

Drugs in the Pipeline for Type 2 Diabetes

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with insulin, and with insulin plus oral antidiabetic agents.21 Overall, the HbA1c-lowering effect of dapagliflozin ranged from 0.35% to 0.90% (change from baseline and placebo subtracted).18-23 In addition, dapagliflozin also had beneficial effects on fasting blood glucose, with reductions from baseline of 10 mg/dL to 25 mg/dL,19,20 as well as postprandial area under the curve, systolic blood pressure (3-6 mm Hg),22 and body weight (0.46-4.5 kg).18-23 Small increases in blood urea nitrogen and hematocrit, as well as a higher risk for reversible genitourinary infections, were seen with dapagliflozin.18-23

The FDA’s Endocrinologic and Metabolic Drugs Advisory Committee (EMDAC) recently (July 19, 2011) reviewed the global clinical development program database for dapagliflozin and voted 9 to 6 against recommending its approval, citing “fears that the product may cause about a 5-fold increase in breast and bladder cancer.”24 Some EMDAC members did not accept the sponsor’s explanation that the increased risk seen in patients taking this drug was preexisting and was likely linked to the study’s uneven subject selection process. Although some analysts suggest that an outside panel of experts will still recommend the approval of dapagliflozin, such an

Table 2 Insulin Preparations Onset timea

Peak timea

Durationa

Insulin aspart (NovoLog)

10-20 min

1-3 hr

3-5 hr

Insulin glulisine (Apidra)

25 min

45-48 min

4-5 hr

Insulin lispro (Humalog)

15-30 min

0.5-2.5 hr

3-6.5 hr

30-60 min

1-5 hr

6-10 hr

Administer 30 min before meals

1-2 hr

6-14 hr

16-24+ hr

Cloudy appearance

Insulin detemir (Levemir)

1.1-2 hr

3.2-9.3 hr

Insulin glargine (Lantus)

1.1 hr

None

24 hr

70% Insulin aspart protamine/30% insulin aspart (NovoLog Mix 70/30)

10-20 min

1-4 hr

24 hr

75% Insulin lispro protamine/25% insulin lispro protamine (Humalog Mix 75/25)

15-30 min

2 hr

22 hr

50% Insulin lispro protamine/50% insulin lispro protamine (Humalog Mix 50/50)

15-30 min

2 hr

22 hr

70% Insulin NPH/30% insulin regular (Humulin 70/30, Novolin 70/30)

30 min

1.5-12 hr

24 hr

50% Insulin NPH/50% insulin regular (Humulin 50/50)

30-60 min

1.5-4.5 hr

7.5-24 hr

Drug (brand)

Comments

Rapid-acting Administer within 15 min before or immediately after meals

Short-acting Insulin regular (Novolin R, Humulin R) Intermediate-acting Insulin NPH (Novolin N, Humulin N) Long-acting 5.7-24 hr Do not mix with (dose-dependent) other insulins

Premixed Cloudy appearance Administer within 15 min before meals

Cloudy appearance Administer within 30 min before meals

a

McEvoy GK, ed. American Society of Health-System Pharmacists Drug Information. Bethesda, MD; 2008.

NPH indicates neutral protamine Hagedorn.

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approval may come with strong warnings about the drug’s potential for risk of malignancy.25 Despite the recent setback from the FDA’s advisory board, the future for this drug class (ie, SGLT2 inhibitors) is promising. Some 4 clinical trials involving SGLT2 inhibitors are currently recruiting patients. Of all the diabetes drugs in the pipeline, SGLT2 inhibitors will most likely be the next class of drugs to be added to the clinician’s armamentarium for the management of patients with type 2 diabetes.

11Beta-Hydroxysteroid Dehydrogenase Type 1 Inhibitors The 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) inhibitor is an enzyme that converts the inert hormone cortisone to its active form, cortisol, in target tissues.26 Excess cortisol can cause insulin resistance by inhibiting pancreatic beta-cell insulin secretion and peripheral glucose uptake, and by promoting gluconeogenesis.27 11beta-HSD1 is up-regulated in adipose tissues of patients with the metabolic syndrome.28 In animal studies, transgenic mice overexpressing 11beta-HSD1 eventually develop glucose intolerance, insulin resistance, dyslipidemia, and hypertension.29,30

Because of its specific role in glucocorticoid interconversion, inhibition of this enzyme can decrease glucocorticoid activity and improve the components involved in the metabolic syndrome. Using 11beta-HSD1–knockout animals, researchers have shown that such inhibition can improve insulin sensitivity, reduce body weight, and lower triglyceride levels.31 In humans, 11beta-HSD1 inhibitors have been shown to improve lipid profiles, fasting glucose levels,32 and hepatic insulin sensitivity.33 The most advanced drug in this class in development is INCB13739.34 In a double-blind placebo-controlled phase 2b clinical trial, 302 patients with type 2 diabetes (mean HbA1c, 8.3%) who had been receiving metformin monotherapy (mean dose, 1.5 g daily) were randomized to receive 1 of 5 doses of INCB13739, or placebo, once daily for 12 weeks.34 After 12 weeks, compared with placebo, patients who received 200 mg of INCB13739 demonstrated significantly lower HbA1c (–0.6%), fasting plasma glucose (–24 mg/dL), and homeostasis model assessment–insulin resistance (–24%). A reversible dose-dependent elevation in adrenocorticotrophic hormone, generally within the normal reference range, was also noted. Therapy with INCB13739 did not change basal cortisol homeo-

Table 3 Drugs in the Pipeline for Type 2 Diabetes Drug category

Mechanism of action

Comments

Sodium-glucose cotransporter-2 inhibitors

Inhibit reabsorption of glucose at the proximal tubule of the kidney, thereby decreasing systemic hyperglycemia

Low potential for hypoglycemia Furthest along in clinical trials

11beta-hydroxysteroid dehydrogenase type 1 inhibitors

Inhibit an enzyme responsible for activating cortisone to cortisol, which minimizes antiglycemic effects of cortisol

Low potential for hypoglycemia All drugs currently in phase 2 clinical trials

Glycogen phosphorylase inhibitors

Inhibit enzymes responsible for hepatic gluconeogenesis

Still very early in development Oral agents have shown promising results in animals and humans

Glucokinase activators

Activate key enzyme to increase hepatic glucose metabolism

Several drugs are currently in phase 2 clinical trials

G protein–coupled receptor 119 agonists

Mechanisms unknown Activation induces insulin release and increases secretion of glucagon-like peptide 1 and gastric inhibitory peptide

Still very early in development Animal data are available

Protein tyrosine phosphatase 1B inhibitors

Increase leptin and insulin release

Still very early in development A potential weight-loss medication

Glucagon-receptor antagonists

Block glucagon from binding to hepatic receptors, thereby decreasing gluconeogenesis

Low potential for hypoglycemia

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stasis, testosterone levels in men, and the free androgen index in women. Adverse events were similar across all treatment groups.34 The 11beta-HSD1 is an interesting drug class that is still in very early stages of development. Available data so far strongly suggest that 11beta-HSD1 inhibitors are potential options for the treatment of type 2 diabetes, although additional clinical testing is needed.35 No drug in this class has entered phase 3 clinical trials.

Glycogen Phosphorylase Inhibitors The liver is central to glucose handling and homeostasis. It accounts for approximately 90% of the body’s endogenous glucose production. In patients with type 2 diabetes, excessive hepatic glucose production, along with insulin resistance, can contribute to hyperglycemia.

Hepatic glucose production has 2 major pathways— glycogenolysis and gluconeogenesis. Inhibition of hepatic glucose production has become the focus of newer antidiabetic agents for the treatment of type 2 diabetes.36 One specific target is glycogen phosphorylase, which catalyzes the phosphorolytic cleavage of glycogen to produce glucose-1-phosphate, which is then isomerized by phosphoglucomutase to glucose-6-phosphate and then enters the glycolytic pathway to produce glucose.36 Creating an inhibitor that specifically targets glycogen phosphorylase would then essentially decrease the amount of glucose produced by the liver.

There are 5 binding sites on the glycogen phosphorylase enzyme that have been found to be potential targets—the catalytic site, inhibitor site, adenosine monophosphate (AMP) allosteric site, glycogen storage site, and a new allosteric binding site.37 Findings from a study by Martin and colleagues show that CP91149 is a glycogen phosphorylase inhibitor that binds to the inhibitor site and reduces plasma glucose levels in mice.38 Martin and colleagues found that oral CP-91149 indirectly inhibits gluconeogenesis via the disruption of glucose/glycogen cycling and inhibits the human liver glycogen phosphorylase a enzyme, thereby improving glucose levels. In addition, CP-91149, which has been characterized in vitro and in vivo, suppressed glycogenolysis in both rat and human liver cells.38 When studying obese mice, the investigators found that a single 50-mg/kg oral dose of CP-91149 reduced plasma glucose concentrations to near-normal levels 3 hours after administration (plasma glucose, 235 ± 21 mg/dL with vehicle vs 134 ± 7 mg/dL with CP-91149).38 Using kinetic experiments, Oikonomakos and colleagues found that the T-state of glycogen phosphorylase b enzyme is the best confirmation to target when looking for glycogen phosphorylase inhibitors.39 They found CP-

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320626 to be an inhibitor of the human liver glycogen phosphorylase by binding at the allosteric site compared with the inhibitor site that CP-91149 binds to, which conforms glycogen phosphorylase to its T-state.39 The development of glycogen phosphorylase inhibitors is promising; continued research to identify other potential targets of hepatic glucose production is needed.

Glucokinase Activators Glucokinase is a monomer that resides in the liver and the pancreas. It determines the rate of glucose metabolism by regulating the amount of insulin produced and released from pancreatic beta-cells in response to the amount of glucose in the blood; elevated levels of glucose will increase glucokinase levels in the pancreas, thereby increasing the release of insulin. In addition, glucokinase influences hepatic lipid metabolism and gluconeogenesis in the liver.40 Glucokinase has been found to function in patients with type 2 diabetes but to a lesser degree than in individuals without diabetes. The development of a compound that would directly affect glucokinase may help to increase the amount of insulin released in those who have insulin deficiency.

According to Grimsby and colleagues, glucokinase in the pancreas is a glucose sensor, causing insulin to be released once blood glucose levels reach a certain threshold, approximately 5 mM.41 Glucokinase in the liver is regulated by a glucokinase regulatory protein, which prevents glucokinase from becoming activated and available until glucose must be metabolized, such as after meals, when insulin must be released to normalize blood glucose. In patients with type 2 diabetes, glucokinase in the liver has been found to be reduced by approximately 50%.42 Using the kinetic activity of glucokinase, recent studies have shown many glucokinase activators (GKAs), including GKAs 1 through 14, that increase the enzymatic activity of glucokinase. GKAs bind to the allosteric site of glucokinase, which increases the maximum velocity and/or glucose affinity of glucokinase via glucose metabolism.43 As mentioned earlier, one possible side effect of GKAs is that they can induce moderate hypoglycemia, because they increase the amount of insulin released. This side effect can be reduced by creating a GKA that has less of an impact on the glucose concentration at half the maximum velocity.43 As a result of the active role that glucokinase plays in glucose homeostasis and, as a glucose sensor, in the release of insulin to decrease blood glucose levels, the development of a drug that can increase the impact or activity of glucokinase looks promising for treating type 2 diabetes.

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G Proteinâ&#x20AC;&#x201C;Coupled Receptor 119 Agonists G proteinâ&#x20AC;&#x201C;coupled receptor 119 (GPR119) is a longchain fatty acid receptor that is chiefly expressed by pancreatic beta-cells.44 The physiologic role of GPR119 remains unknown. Even so, its function has been elucidated through GPR119 agonists that have been shown to couple to Gas.44 Upon activation by an agonist ligand, GPR119 increases cyclic AMP (cAMP) and induces insulin release. Indirectly, activating GPR119 also stimulates the release of incretins glucagon-like peptide (GLP)-1 and gastric inhibitory peptide. Taken together, GPR119 agonists may act as a potential target for glycemic control in patients with type 2 diabetes through direct insulinotropic effects and indirectly through incretin release.44 Using in situ hybridization analysis, Chu and colleagues demonstrated that GPR119 was highly expressed by beta-cell islet population.44 To determine the significance of GPR119 in glucose homeostasis, the investigators used the highly selective GPR119 agonist AR231453. They found that AR231453 significantly increased cAMP levels in HEK 293 cells, suggesting that GPR119 couples to Gas.44 Moreover, to demonstrate that AR231453 effectively stimulated GPR119 endogenously, the hamster beta-cell line HIT-T15 expressing GPR119 was used, which in the presence of AR231453 increased cAMP levels.

In addition, the cAMP levels increased in the presence of only a modest amount of glucose, indicating that GPR119 agonists are glucose-dependent for activation.44 Using a model involving GPR119 beta-cellâ&#x20AC;&#x201C;expressing mice with type 2 diabetes, the investigators demonstrated a significant improvement in glucose tolerance by enhancement of glucose-dependent insulin release.

However, in mice with GPR119 gene deletion from the X-chromosome, AR231453 had no effect on glucose levels.44 Surprisingly, Chu and colleagues showed that oral treatment with a GPR119 agonist AR231453 provided better glycemic control than intravenous treatment, which suggests possible incretin involvement.44 Adding to these results, Yoshida and colleagues confirmed that the GPR119 agonist AS1907417 is effective in preserving beta-cells and controlling glucose levels in HEK293 cells expressing human GPR119.45 Furthermore, Flock and colleagues demonstrated that AR231453 not only directly increases insulin, incretin, and GLP-1 levels but also, independently of incretins, slows gastric emptying.46 Overall, GPR119 agonists, by activating several complementary pathways, may provide a mechanism for glucose control in patients with type 2 diabetes.

Protein Tyrosine Phosphatase 1B Inhibitors Protein tyrosine phosphatase (PTP) 1B inhibitors

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may be a possible oral therapeutic target for glycemic control and weight management through sustained insulin and leptin release in patients with type 2 diabetes. PTP1B is part of the protein tyrosine phosphatase family that is found ubiquitously in cells whose function is the removal of a phosphate group from the tyrosine phosphate receptor. In the insulin cascade, a cytosolic protein tyrosine phosphatase negatively controls insulin release by the dephosphorylation of several of the insulin receptor kinase substrates.47 In addition, PTP1B inhibitors play a role in downregulation of leptin signaling by dephosphorylating Janus kinase 2 found downstream of the leptin receptor.48 As a result of its involvement in increasing insulin and leptin sensitivity and improving glucose homeostasis, PTP1B may be an oral therapeutic alternative for patients who have type 2 diabetes with functioning beta-cells.

PTP1B has been shown to be an important part in the insulin and leptin signaling pathway. A study with PTP1B-knockout mice demonstrated resistance to obesity and increased insulin sensitivity.49 In a recent study in monkeys, inhibition of PTP1B with antisense oligonucleotides led to improved insulin sensitivity.50 Along with peripheral tissues, neuronal PTP1B has also been implicated in controlling adiposity and leptin sensitivity.51 Many PTP1B inhibitors are being manufactured and studied. However, the drawbacks of PTP1B inhibitors include their low affinity to and selectivity for the enzyme and their difficulty with membrane permeability.48 The catalytic domain contains 2 negative charges, therefore making charged ligands preferred for affinity and selectivity. Charged molecules have decreased membrane permeability. One strategy enlisted to increase membrane permeability has been the addition of a hydrophobic region.52 More research is needed to determine the best strategy for delivery of the inhibitor to the cytosol and to determine the selectivity of that inhibitor for PTP1B to achieve the most benefit from oral PTP1B inhibitor therapy.

Glucagon-Receptor Antagonists Glucagon is a peptide hormone secreted by alphacells in the pancreas. It raises blood glucose by enhancing glycogenolysis and gluconeogenesis through the activation of cAMP-dependent protein kinase cascade in the liver, and it is the primary counterregulatory hormone to insulin.53 When excess glucagon is secreted, a process frequently seen in type 2 diabetes, fasting and postprandial hyperglycemia ensues.54,55 Accordingly, new therapeutic agents that can block glucagon action could lower fasting and postprandial blood glucose and potentially emerge as a new drug class in the treatment of type 2 diabetes.

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Although many glucagon-receptor antagonists have been developed and tested over the past 20 years, only one human study had been published. Bay 27-9955, a nonpeptide compound that competitively blocks the interaction of glucagon with the human glucagon receptor, was tested in 8 normal volunteers in a double-blind, placebo-controlled, crossover study. A single dose of 200 mg was able to block the effect of exogenous glucagon, thereby stabilizing plasma glucose concentrations and the rate of glucose production in the study participants.56 The future for this drug class is uncertain, because of the limited published human data currently available.

Much more information is needed to elucidate the efficacy and safety of this potential treatment.

Conclusion Diabetes is a complex and costly disease. Although a cure is not imminent, many treatment options are currently available to aid in the control and management of this disease that is continuing to increase in the United States. However, despite this abundance of therapeutic options, the majority of American patients with type 2 diabetes are not achieving appropriate glycemic control.

Novel therapies are in various stages of development, and some are showing promising results in clinical trials.

Adding new options with new mechanisms of action to the treatment armamentarium may eventually help improve outcomes and reduce the cost burden of this condition. It is prudent to remain optimistic as the research in this field continues to evolve. ■ Author Disclosure Statement Dr Quang Nguyen, Ms Thomas, Ms Lyons, Dr Loida Nguyen, and Dr Plodkowski have nothing to disclose.

References 1. Danaei G, Finucane MM, Lu Y, et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systemic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants. Lancet. 2011;378:31-40.

2. Centers for Disease Control and Prevention. National diabetes fact sheet: national estimates and general information on diabetes and prediabetes in the United States, 2011. www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf. Accessed July 30, 2011.

3. Krishnarajah G, Bhosle M, Chapman R. Health care costs associated with treatment modification in type 2 diabetes mellitus patients taking oral anti-diabetic drugs.

Manag Care. 2011;20:42-48.

4. Alexander GC, Sehgal NL, Moloney RM, et al. National trends in treatment of type 2 diabetes mellitus, 1994-2007. Arch Intern Med. 2008;168:2088-2094.

5. IMS Institute for Healthcare Informatics. The Use of Medicines in the United States: Review of 2010. April 2011. www.imshealth.com/deployedfiles/imshealth/ Global/Content/IMS%20Institute/Static%20File/IHII_UseOfMed_report.pdf.

Accessed July 31, 2011.

6. Kelland K, Beasley D. Global diabetes epidemic balloons to 350 million. June 25, 2011. www.reuters.com/assets/print?aid=USTRE75O1F220110625. Accessed July 30, 2011.

7. IMS Institute for Healthcare Informatics. The Global Use of Medicines: Outlook Through 2015. May 2011. www.imshealth.com/deployedfiles/ims/Global/Content/ Insights/IMS%20Institute%20for%20Healthcare%20Informatics/Global_Use_of_ Medicines_Report.pdf. Accessed July 31, 2011.

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8. National Institute of Diabetes and Digestive and Kidney Diseases. Fact sheet: type 2 diabetes. Updated October 2010. http://report.nih.gov/NIHfactsheets/Pdfs/Type2 Diabetes(NIDDK).pdf. Accessed July 30, 2011.

9. Koro CE, Bowlin SJ, Bourgeois N, Fedder DO. Glycemic control from 1988 to 2000 among U.S. adults diagnosed with type 2 diabetes: a preliminary report. Diabetes Care.

2004;27:17-20.

10. Gerich JE, Meyer C, Woerle HJ, et al. Renal gluconeogenesis: its importance in human glucose homeostasis. Diabetes Care. 2001;24:382-391.

11. Wright EM, Hirayama BA, Loo DF. Active sugar transport in health and disease.

J Intern Med. 2007;261:32-43.

12. Wright EM. Renal Na(+)-glucose cotransporters. Am J Physiol Renal Physiol.

2001;280:F10-F18.

13. Thomson AB, Wild G. Adaptation of intestinal nutrient transport in health and disease. Dig Dis Sci. 1997;42:453-469,470-488.

14. Bakris GL, Fonseca VA, Sharma K, et al. Renal sodium-glucose transport: role in diabetes mellitus and potential clinical implications. Kidney Int. 2009;75:1272-1277.

15. Rahmoune H, Thompson PW, Ward JM, et al. Glucose transporters in human renal proximal tubular cells isolated from the urine of patients with non-insulindependent diabetes. Diabetes. 2005;54:3427-3434.

16. Freitas HS, Anhê GF, Melo KF, et al. Na(+)-glucose transporter-2 messenger ribonucleic acid expression in kidney of diabetic rats correlates with glycemic levels: involvement of hepatocyte nuclear factor-1alpha expression and activity.

Endocrinology. 2008;149:717-724.

17. ClinicalTrials.gov. http://clinicaltrials.gov/ct2/results?term=SGLT2+inhibitors.

Accessed July 31, 2011.

18. Komoroski B, Vachharajani N, Boulton D, et al. Dapagliflozin, a novel SGLT2 inhibitor, induces dose-dependent glucosuria in healthy subjects. Clin Pharmacol Ther. 2009;85:520-526.

19. Bailey CJ, Gross JL, Pieters A, et al. Effect of dapagliflozin in patients with type 2 diabetes who have inadequate glycaemic control with metformin: a randomised, double-blind, placebo-controlled trial. Lancet. 2010;375:2223-2233.

20. Strojek K, Yoon K, Hruba V, et al. Effect of dapagliflozin in patients with type 2 diabetes who have inadequate glycaemic control with glimepiride: a randomised, 24week, double-blind, placebo-controlled trial. Diabetes Obes Metab. 2011 Jun 15. Epub ahead of print.

21. Wilding JP, Norwood P, T’joen C, et al. A study of dapagliflozin in patients with type 2 diabetes receiving high doses of insulin plus insulin sensitizers: applicability of a novel insulin-independent treatment. Diabetes Care. 2009;32:1656-1662.

22. List JF, Woo V, Morales E, et al. Sodium-glucose cotransport inhibition with dapagliflozin in type 2 diabetes. Diabetes Care. 2009;32:650-657.

23. Bailey CJ. Renal glucose reabsorption inhibitors to treat diabetes. Trends Pharmacol Sci. 2011;32:63-71. Epub 2011 Jan 4.

24. Lowry F. FDA panel says no to new antidiabetes agent. July 19, 2011. www.medscape.com/viewarticle/746654. Accessed July 31, 2011.

25. Martino M. FDA staffers: AZ, BMS diabetes drug dapagliflozin has risks. July 15, 2011. www.fiercebiotech.com/story/fda-staffers-az-bms-diabetes-drug-dapagliflozinhas-risks/2011-07-15. Accessed July 31, 2011.

26. Oppermann UC, Persson B, Jornvall H. Function, gene organization and protein structures of 11beta-hydroxysteroid dehydrogenase isoforms. Eur J Biochem. 1997; 249:355-360.

27. Sapolsky RM, Romero LM, Munck AU. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions.

Endocr Rev. 2000;21:55-89.

28. Wamil M, Seckl JR. Inhibition of 11beta-hydroxysteroid dehydrogenase type 1 as a promising therapeutic target. Drug Disc Today. 2007;12:504-520.

29. Masuzaki H, Yamamoto H, Kenyon CJ, et al. Transgenic amplification of glucocorticoid action in adipose tissue causes high blood pressure in mice. J Clin Invest.

2003;112:83-90.

30. Masuzaki H, Paterson J, Shinyama H, et al. A transgenic model of visceral obesity and the metabolic syndrome. Science. 2001;294:2166-2170.

31. Wang M. Inhibitors of 11beta-hydroxysteroid dehydrogenase type 1 for the treatment of metabolic syndrome. Curr Opin Invest Drugs. 2006;7:319-323.

32. Ge R, Huang Y, Liang G, Li X. 11B-hydroxysteroid dehydrogenase type 1 inhibitors as promising therapeutic drugs for diabetes: status and development. Curr Med Chem. 2010;17:412-422.

33. Andrews RC, Rooyackers O, Walker BR. Effects of the 11beta-hydroxysteroid dehydrogenase inhibitor carbenoxolone in insulin sensitivity in men with type 2 diabetes. J Clin Endocrinol Metab. 2003;88:285-291.

34. Rosenstock J, Banarer S, Fonseca VA, et al. The 11-beta-hydroxysteroid dehydrogenase type 1 inhibitor INCB13739 improves hyperglycemia in patients with type 2 diabetes inadequately controlled by metformin monotherapy. Diabetes Care. 2010; 33:1516-1522.

35. Wang M. Inhibitors of 11β-HSD1 in antidiabetic therapy. Handb Exp Pharmacol.

2011;203:127-146.

36. Henke BR, Sparks SM. Glycogen phosphorylase inhibitors. Mini Rev Med Chem.

2006;6:845-857.

37. McCormack JG, Westergaard N, Kristiansen M, et al. Pharmacological approaches to inhibit endogenous glucose production as a means of anti-diabetic therapy. Curr Pharm Des. 2001;7:1451-1474.

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38. Martin WH, Hoover DJ, Armento SJ, et al. Discovery of a human liver glycogen phosphorylase inhibitor that lowers blood glucose in vivo. Proc Natl Acad Sci U S A. 1998;95:1776-1781.

39. Oikonomakos NG, Skamnaki VT, Tsitsanou KE, et al. A new allosteric site in glycogen phosphorylase b as a target for drug interactions. Structure. 2000;8:575-584.

40. Matschinsky FM, Porte D Jr. Glucokinase activators (GKAs) promise a new pharmacotherapy for diabetics. F1000 Med Rep. 2010;2:43.

41. Grimsby J, Berthel SJ, Sarabu R. Glucokinase activators for the potential treatment of type 2 diabetes. Curr Top Med Chem. 2008;8:1524-1532.

42. Caro JF, Triester S, Patel VK, et al. Liver glucokinase: decreased activity in patients with type II diabetes. Horm Metab Res. 1995;27:19-22.

43. Matschinsky FM, Zelent B, Doliba N, et al. Glucokinase activators for diabetes therapy. May 2010 status report. Diabetes Care. 2011;34(suppl 2):S236-S243.

44. Chu ZL, Jones RM, He H, et al. A role for beta-cell-expressed G protein-coupled receptor 119 in glycemic control by enhancing glucose-dependent insulin release.

Endocrinology. 2007;148:2601-2609.

45. Yoshida S, Tanaka H, Oshima H, et al. AS1907417, a novel GPR119 agonist, as an insulinotropic and β-cell preservative agent for the treatment of type 2 diabetes.

Biochem Biophys Res Commun. 2010;400:745-751.

46. Flock G, Holland D, Seino Y, et al. GPR119 regulates murine homeostasis through incretin receptor-dependent and independent mechanisms. Endocrinology.

2011;152:337-383.

47. Salmeen A, Andersen JN, Myers MP, et al. Molecular basis for the dephosphorylation of the activation segment of the insulin receptor by protein tyrosine phos-

phatase 1B. Mol Cell. 2000;6:1401-1412.

48. Popov D. Novel protein tyrosine phosphatase 1B inhibitors: interaction requirements for improved intracellular efficacy in type 2 diabetes mellitus and obesity control. Biochem Biophys Res Commun. 2011;410:377-381.

49. Elchebly M, Payette P, Michaliszyn E, et al. Increased insulin sensitivity and obesity resistance in mice lacking the protein tyrosine phosphatase-1B gene. Science.

1999;283:1544-1548.

50. Swarbrick MM, Havel PJ, Levin AA, et al. Inhibition of protein tyrosine phosphatase-1B with antisense oligonucleotides improves insulin sensitivity and increases adiponectin concentrations in monkeys. Endocrinology. 2009;150:1670-1679.

51. Martin TL, Alquier T, Asakura K, et al. Diet-induced obesity alters AMP kinase activity in hypothalamus and skeletal muscle. J Biol Chem. 2006;281:18933-18941.

52. Ottanà R, Maccari R, Ciurleo R, et al. 5-Arylidene-2-phenylimino-4-thiazolidinediones as PTP1B and LMW-PTP inhibitors. Bioorg Med Chem Lett. 2009;17:1928-1937.

53. MacNeil DJ, Occi JL, Strader CD, et al. Cloning and expression of a human glucagon receptor. Biochem Biophys Res Commun. 1994;198:328-334.

54. Shah P, Vella A, Basu A, et al. Lack of suppression of glucagon contributes to postprandial hyperglycemia in subjects with type 2 diabetes mellitus. J Clin Endocrinol Metab. 2000;85:4053-4059.

55. Knop FK, Vilsbøll T, Hojberg PV, et al. Reduced incretin effect in type 2 diabetes: cause or consequence of the diabetic state? Diabetes. 2007;56:1951-1959.

56. Petersen KF, Sullivan JT. Effects of a novel glucagon receptor antagonist (Bay 279955) on glucagon-stimulated glucose production in humans. Diabetologia. 2001; 44:2018-2024.

STAKEHOLDER PERSPECTIVE New Therapies with Novel Mechanisms of Action Are Urgently Needed for Type 2 Diabetes MEDICAL DIRECTORS: Type 2 diabetes mellitus is currently an area that supports a worldwide “growth industry” in the worst sense of the term. The prevalence of this systemic metabolic disorder continues to rise exponentially as the world’s population struggles with ongoing and worsening imbalances between increasing caloric intake and decreasing caloric expenditure, especially in individuals with concomitant insulin resistance.

The consequences of type 2 diabetes are burdensome for all patients with this disease and potentially fatal for a sizable fraction of diabetic patients, because the risks for renal failure, cardiovascular disease, and lower-extremity amputations are dramatically increased in this patient population compared with the age-matched risk in individuals free of diabetes.

DRUG MANUFACTURERS: This epidemic of patients with diabetes has led to a phenomenal proliferation in the number of medications available to treat the disease, with dramatic increases in the number of

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both oral and injectable preparations. Nevertheless, despite this pharmacologic cornucopia, the majority of patients with type 2 diabetes still do not have their blood glucose levels under adequate control.

Therefore, there remains a significant need for additional classes of medications that can work through novel mechanisms of action to improve the control of blood glucose levels in patients whose levels are not being controlled with currently available medications. The emerging classes of antidiabetic medications discussed in this article by Nguyen and colleagues afford the hope that we may eventually be able to obtain better pharmacologic control of the runaway blood glucose that bedevil so many of our diabetic patients.

James V. Felicetta, MD Chairman, Department of Medicine Carl T. Hayden Veterans Affairs Medical Center Phoenix, AZ

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REVIEW ARTICLE

Lipid Management in Patients with Type 2 Diabetes Marsha J. Daniel, PharmD, cPh, CDE

Stakeholder Perspective, page 321

Am Health Drug Benefits.

2011;4(5):312-322 www.AHDBonline.com Disclosures are at end of text

Background: Diabetes is correlated with a high risk for cardiovascular disease (CVD). The management of diabetic dyslipidemia, a well-recognized and modifiable risk factor, is a key element in the multifactorial approach to preventing CVD in patients with type 2 diabetes. Diabetic dyslipidemia is characterized by elevated triglyceride levels, decreased high-density lipoprotein cholesterol levels, and elevated low-density lipoprotein cholesterol (LDL-C) levels.

Objectives: To describe the effective approach to the management of dyslipidemia in patients with diabetes to allow providers and payers to become familiar with the treatment goals for all the components of lipoproteins, to correctly initiate appropriate lipid-lowering medications based on treatment goals and lipid-lowering capability, and to apply the data presented in lipid clinical trials to the treatment of patients with diabetes.

Summary: Diabetes is associated with a 2- to 4-fold increase in risk for CVD. The risk factors for coronary artery disease (CAD) include hypertension, dyslipidemia, obesity, and smoking. Therefore, prioritizing and managing diabetic patients with CVD risk factors is vital.

Conclusion: LDL-C appears to have the greatest role in premature and early atherosclerosis and the development of CAD and must be treated as aggressively as hyperglycemia to reduce CAD risk. Becoming familiar with lipid treatment goals and the many therapies available today can help providers and payers implement the appropriate approach to managing diabetic dyslipidemia risk factors and reduce the burden of this disease.

T

aggressively as hyperglycemia to reduce CAD risk. In fact, improved control of LDL-C can reduce cardiovascular complications by 20% to 50%.5

Dr Daniel is Clinical Pharmacist, Cleveland Clinic Florida, Weston.

Diabetic Dyslipidemia Diabetic dyslipidemia is characterized by elevated triglycerides, decreased high-density lipoprotein cholesterol (HDL-C), and elevated LDL-C in comparison with patients without diabetes. HDL-C is responsible for removing excess cholesterol from the peripheral tissues.1-4 Therefore, when HDL-C is decreased, triglycerides, very low-density lipoprotein cholesterol (VLDLC), and LDL-C levels will all be elevated.1-4 The particle size of LDL-C contributes to these elevations. In patients with diabetes, the particle size of LDL-C is much smaller and denser because of elevated triglyceride levels, which in turn contributes to a 3-fold increase in the risk for developing CAD. The mechanism responsible for this process is triggered by the particlesâ&#x20AC;&#x2122; ability to enter the blood vessels much more quickly than do normal, large, and less-dense LDL-C particles, thereby increasing the risk for thrombosis.1 Elevated triglyceride levels can arise from 2 abnormalitiesâ&#x20AC;&#x201D;overproduction of VLDL-C and impaired

he prevalence of diabetes has increased dramatically in recent decades. This trend highlights the importance of prevention and appropriate therapy to reduce cardiovascular events in patients with diabetes. Reaching adequate blood glucose control is important in decreasing microvascular complications associated with diabetes; however, good lipid management is vital for reducing the incidence of cardiovascular events in patients with diabetes.1-4 Cardiovascular disease (CVD) has been recognized as the most frequent cause of morbidity and mortality among those with diabetes. Diabetes is associated with a 2- to 4-fold increased risk for CVD and is identified as a coronary artery disease (CAD) risk equivalent.1-4 The risk factors for CAD include hypertension, dyslipidemia, obesity, and smoking.1-3 Therefore, prioritizing and managing diabetic patients with CVD risk factors is extremely important. In dyslipidemia, serum low-density lipoprotein cholesterol (LDL-C) appears to have the greatest role in premature and early atherosclerosis and CAD development and must therefore be treated as

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lipolysis of triglycerides. Patients with type 2 diabetes have an overproduction of triglyceride-rich VLDL-C level, which is a result of high free fatty acid levels, hyperglycemia, obesity, and insulin resistance. In fact, approximately 30% to 40% of patients with diabetes have triglyceride levels >200 mg/dL, and 10% of patients have triglyceride levels >400 mg/dL.1-4

LDL-C Treatment Goals Lowering LDL-C is the main goal of treatment. The specific LDL-C treatment goals are outlined in Table 1.

Once the LDL-C goal is attained, other lipid and nonlipid risk factors can be addressed. Therapeutic lifestyle changes are considered first-line therapy and should be continued for at least 3 months before initiating pharmacotherapy.6 Drug therapy should be reserved for patients who are at increased risk for CAD or for those in whom lifestyle changes alone are ineffective. The Framingham risk scoring system should be used for individuals with no evidence of CAD but with 2 or more major risk factors for CAD other than LDL-C.6,7 In high-risk individuals, the initiation of drug therapy

KEY POINTS ➤

➤

➤

➤

➤

Diabetes is correlated with a high risk for cardiovascular disease (CVD).

Managing diabetic dyslipidemia—characterized by elevated triglycerides, decreased high-density lipoprotein cholesterol (HDL-C), and elevated lowdensity lipoprotein cholesterol (LDL-C) levels— is a crucial aspect of the multifactorial approach to preventing CVD in patients with type 2 diabetes.

LDL-C has the greatest role in early atherosclerosis and must be treated as aggressively as hyperglycemia to reduce coronary artery disease risk.

Providers and payers must become familiar with current treatment lipid goals, including the management of elevated LDL-C levels, reduced HDL-C levels, and elevated triglyceride levels.

Therapeutic lifestyle changes should be attempted before instituting pharmacotherapy. The appropriate use of the many medications available for diabetic dyslipidemia can help reduce the burden of this disease and the risk for CVD.

Table 1 Current LDL-C Treatment Goals LDL-C threshold for initiating TLCs

LDL-C threshold for drug therapy

Risk category

LDL-C goal

CHD risk equivalents, 10-yr risk >20%: • Age >45 yrs in men, >55 yrs in women • Smoking • HTN or taking antihypertensives • HDL-C <35 mg/dL • Diabetes • Family history of CHD

<100 mg/dL Optional, <70 mg/dL

≥100 mg/dL

≥100 mg/dL For <100 mg/dL, consider initiating or intensifying LDL-C–lowering therapy Treat other risk factors or use other lipid-modifying drugs if high TG or low HDL-C

2+ risk factors (10-yr risk, 10%-20%)

<130 mg/dL Optional, <100 mg/dL

≥130 mg/dL

≥130 mg/dL For 100-129 mg/dL, consider LDL-C– lowering therapy

2+ risk factors (10-yr risk <10%)

<130 mg/dL

≥130 mg/dL

≥160 mg/dL

0-1 risk factor (10-yr risk not needed)

<160 mg/dL

≥160 mg/dL

≥190 mg/dL For 160-189 mg/dL, drug therapy is optional Consider therapy if single severe risk factor, multiple life habits and/or emerging risk factors, or 10-yr risk is nearly 10%

NOTE: Use the Framingham scoring system to identify those with a 10-year risk.

CHD indicates chronic heart disease; HDL-C, high-density lipoprotein cholesterol; HTN, hypertension; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; TLCs, therapeutic lifestyle changes.

Source: Reference 6.

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Table 2 LDL-C versus Non–HDL-C Treatment Goals Risk category

LDL-C goal

Non–HDL-Ca goal

CHD and CHD risk equivalents <100 mg/dL (10-yr risk >20%)

<130 mg/dL

2+ risk factors (10-yr risk ≤20%) <130 mg/dL

<160 mg/dL

0-1 risk factor

<190 mg/dL

<160 mg/dL

a Total cholesterol minus HDL-C. CHD indicates chronic heart disease; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.

Source: Reference 6.

Table 3 Management of High Triglycerides Classification Normal

TG level

On top of achieving target LDL-C goal

<150 mg/dL

Borderline high

150-199 mg/dL Reduce weight, increase physical activity

High

200-499 mg/dL Intensify LDL-C–lowering therapy or initiate nicotinic acid or a fibrate

Very high

≥500 mg/dL

Goal is to prevent acute pancreatitis through TGlowering by using very-low-fat diets, weight reduction, increased physical activity, and a TG-lowering agent When TG level is ≤500 mg/dL, focus on lowering LDL-C

LDL-C indicates low-density lipoprotein cholesterol; TG, triglyceride.

Source: Reference 6.

should be considered to achieve the non–HDL-C goal (Table 2).6 This can be accomplished by intensifying therapy with an LDL-C–lowering drug or by adding nicotinic acid or a fibrate.

Elevated triglyceride levels is an independent risk factor for CAD. For all patients with high triglyceride levels, the primary goal of therapy is to achieve the target goal for LDL-C (Table 3).6

Management of Low HDL-C Low HDL-C (<40 mg/dL) is a strong predictor of CAD.6 However, there is no specific goal for increasing

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HDL-C. After the LDL-C goal is achieved, weight loss and increased physical activity should be emphasized, and non–HDL-C levels should be evaluated if the triglyceride level is high. If the triglyceride level is at goal, medications for raising HDL-C, such as fibrates or nicotinic acid, should be considered.

Pharmacologic Treatment HMG-CoA Reductase Inhibitors (Statins) The 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) reductase inhibitors, or statins, are the most extensively used lipid-lowering medications and are often the first choice for the treatment of diabetic dyslipidemia (Table 4).1 Statins primarily lower LDL-C levels, but they also have the secondary effects of lowering triglyceride and increasing HDL-C levels. Furthermore, statins may increase the particle size of LDL-C to allow less circulation of smaller, dense LDL-C.1 Mechanism of action. Statins competitively inhibit HMG-CoA reductase, converting HMG-CoA to mevalonate in the hepatic synthesis of cholesterol; the overall result is decreased levels of endogenous cholesterol.

Because of the decreased endogenous cholesterol levels, LDL-C receptor synthesis is activated, resulting in enhanced clearance of circulating LDL-C.1 Dosing and administration. Statins are generally administered in the evening (with or without food) or at bedtime to coincide with the time of day when cholesterol synthesis generally occurs. Initial therapy starts with a lower dose and is generally titrated every 4 to 6 weeks as warranted to achieve the necessary maximum dosage and to decrease the risk for adverse effects.1 Precautions, contraindications. Statins are contraindicated in pregnant and breastfeeding women and should be used with caution in patients with impaired renal/hepatic function.1 Adverse effects. Overall, statins are well tolerated and have negligible adverse effects. The more common adverse effects are headache, nonspecific muscle and joint pain, nausea, diarrhea, constipation, flatulence, and abdominal pain. Significant elevation of liver enzymes can occur, and the discontinuation of treatment is recommended when liver enzymes reach ≥3 times the upper limit of normal.1 Myopathy, a disease of muscle, and rhabdomyolysis, the breakdown of striated muscle, have been reported in 1% to 5% of patients taking statins.1 Patients are encouraged to immediately report any unexplained muscle weakness, tenderness, pain, or fever. An elevated serum creatinine kinase—between 450 IU/L and >1000 IU/L, which is 3 to 10 times the upper limits of normal—can be observed in myopathy or myositis, respectively.1 Rhabdomyolysis, a more severe adverse effect, typi-

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Table 4 Comparing Lipid-Lowering Effects of Statins and Daily Cost of Therapy

Drug (brand)

Daily dose, costa

Total cholesterol change from LDL-C change TG change from HDL-C change baseline, % from baseline, % baseline, % from baseline, %

Atorvastatin (Lipitor) 10 mg, $3.66

–29

–39

–19

6

20 mg, $4.99

–33

–43

–26

9

40 mg, $4.99

–37

–50

–29

6

80 mg, $4.99

–45

–60

–37

5

20 mg, $3.91

–17

–22

–12

3

40 mg, $3.63

–19

–25

–14

4

40 mg bid, $7.26

–27

–36

–18

6

XL, 80 mg, $4.82

–25

–35

–19

7

10 mg, $1.06

–16

–21

–10

5

20 mg, $0.76

–17

–24

–10

6

40 mg, $1.19

–22

–30

–14

7

40 mg bid, $2.38

–29

–40

–19

9

10 mg, $0.63

–16

–22

–11

7

20 mg, $0.93

–24

–32

–15

12

40 mg, $0.86

–25

–34

–20

15

80 mg, $3.99

–27

–37

–19

3

5 mg, $5.16

–33

–45

–35

13

10 mg, $5.16

–36

–52

–10

14

20 mg, $5.19

–40

–55

–28

8

40 mg, $5.23

–46

–63

–2

10

5 mg, $0.59

–19

–26

–12

10

10 mg, $0.66

–23

–30

–15

12

20 mg, $0.93

–28

–38

–19

8

40 mg, $0.93

–31

–41

–18

9

80 mg, $1.19

–36

–47

–24

8

1 mg, $3.65

–23

–32

–15

8

2 mg, $3.65 4 mg, $3.65

–26 –31

–36 –43

–19 –18

7 5

Fluvastatin (Lescol)

Lovastatin (Mevacor)

Pravastatin (Pravachol)

Rosuvastatin (Crestor)

Simvastatin (Zocor)

Pitavastatin (Livalo)

a

Cost as reported by drugstore.com.

HDL-C indicates high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride.

Adapted with permission from Cornell S, Vito CJ. Pharmacologic therapies: dyslipidemia and hypertension in persons with diabetes. In: Mensing C, ed. The Art and Science of Diabetes Self-Management Education: A Desk Reference for Healthcare Professionals. Chicago, IL: American Association of Diabetes Educators; 2006:399-412.

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Table 5 Lipid-Lowering Effects of Bile Acid Sequestrants

Drug (brand)

Daily dose, cost

Total cholesterol, change from LDL-C, change TG, change from HDL-C, change baseline, % from baseline, % baseline, % from baseline, %

Cholestyramine (Questran) 4-8 g bid, $4.08

N/A

–15 to –30

5-10

3-5

30 g (powder), $2.86

N/A

–15 to –30

5-10

3-5

16 g (tablets), $0.88

N/A

–15 to –30

5-10

3-5

3.8 g (powder), $8.10

–7

–15

10

3

1875 mg bid, $0.75

–7

–15

10

3

Colestipol (Colestid)

Colesevelam (Welchol)

HDL-C indicates high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; N/A, not available; TG, triglyceride.

Sources: Reference 1; www.drugstore.com.

cally presents with additional symptoms, including weight gain from fluid retention, fever, nausea, tachycardia, and dark-colored urine.1 Drug interactions. Most statins are metabolized via the cytochrome (CY) P450 3A4 pathway in the liver.

Medications and foods, such as grapefruit juice (>8 oz daily), that are also metabolized through the CYP450 3A4 system should be monitored for increased levels and risks for adverse reactions.1 Monitoring. A baseline lipid profile, serum creatinine kinase, liver function tests, and serum creatinine should be obtained before initiating statin therapy. Monitoring lipid profiles and liver function tests should be conducted every 3 months in the first 6 months of treatment and periodically thereafter. Serum creatinine kinase levels should be checked if a patient reports any muscle pain or discomfort.1 New safety precautions for simvastatin. On June 8, 2011, the US Food and Drug Administration (FDA) recommended new limits for the use of simvastatin 80 mg, because of increased risk of muscle damage.8 Therefore, simvastatin 80 mg should be used only in patients who have been taking this dose for 12 months or more without evidence of myopathy. Simvastatin 80 mg should not be started in new patients, including those already taking lower doses of the drug.8 In addition to these new limitations, the FDA also required the simvastatin label to include new contraindications and dose limitations for using simvastatin with certain medicines.8 Furthermore, as of that time, simvastatin is contraindicated with itraconazole, ketoconazole, posaconazole, erythromycin, clarithromycin, telithro-

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mycin, HIV protease inhibitors, nefazodone, gemfibrozil, cyclosporine, and danazol.8 Also, simvastatin daily doses should not exceed 10 mg when coadministered with amiodarone, verapamil, or diltiazem. (These drugs are contraindicated with niacin/ simvastatin, because that combination is only available with simvastatin 20 or 40 mg.) A simvastatin daily dose of 20 mg should not be exceeded when used concurrently with amlodipine or with ranolazine.8

Bile Acid Sequestrants LDL-C is the primary lipoprotein affected by bile acid sequestrants (Table 5), which also produce a secondary effect of a small increase in HDL-C. Bile acid sequestrants often increase triglycerides, which are already elevated in many patients with diabetes. Therefore, bile acid sequestrants should be avoided as monotherapy in patients with high triglycerides (>250 mg/dL).1 Mechanism of action. Bile acid sequestrants bind to bile acids in the intestinal lumen, thereby decreasing the production of cholesterol. They also inhibit enterohepatic circulation of bile acids and increase the elimination of fecal acid steroids, resulting in a decrease in LDL-C.1 Dosing and administration. Bile acid sequestrants can be dosed once or twice daily. Lower doses are initiated and can be titrated up every 1 to 2 months, as warranted, to achieve the optimal or maximum dose. Tablets should be swallowed whole and taken with plenty of fluid.1 Precautions and contraindications. Colesevelam is listed as pregnancy category B, which indicates that there is no evidence of risk to humans. Cholestyramine and colestipol are listed as pregnancy category C, indi-

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Table 6 Lipid-Lowering Effect of Cholesterol Absorption Inhibitor

Drug (brand) Ezetimibe (Zetia)

Daily dose, cost

Total cholesterol change from baseline, %

LDL-C change from baseline, %

TG change from baseline, %

HDL-C change from baseline, %

10 mg, $4.50

â&#x20AC;&#x201C;13

â&#x20AC;&#x201C;18

â&#x20AC;&#x201C;8

1

HDL-C indicates high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride.

Sources: Reference 1; www.drugstore.com.

cating that risk cannot be ruled out. Bile acid sequestrants are contraindicated when the triglyceride level is >400 mg/dL with primary biliary cirrhosis and bowel and biliary obstructions. Caution should be used in patients with renal insufficiency, volume depletion, and chronic constipation.1 Adverse effects. Most adverse effects are gastrointestinal (GI), because of a lack of systemic absorption. The most common adverse effects are headache, unpalatable taste, nausea, bloating, flatulence, and constipation.1 Drug interactions. Bile acid sequestrants can bind to other medications, resulting in decreased absorption of the other medications and in clinically significant drug interactions. Therefore, it is advised to separate bile acid sequestrants from other medications by administering them 1 hour before or 4 hours after the bile acid sequestrants. Prolonged use of bile acid sequestrants may result in a decrease in absorption of fat-soluble vitamins and folic acid.1 Monitoring. A baseline lipid profile, with a follow-up at 4 to 6 weeks for efficacy, is advised. Electrolytes should be routinely checked, because imbalances have been reported. Prolonged use of bile acid sequestrants may produce hyperchloremic acidosis. Because of the GI adverse effects reported with bile acid sequestrants, patient compliance should be assessed at every visit.1

Cholesterol Absorption Inhibitors The primary effect of cholesterol absorption inhibitors is evaluated in the decrease of LDL-C; however, small decreases in triglyceride levels and increases in HDL-C may be noticed. Cholesterol absorption inhibitors are often prescribed in combination with statins to enhance the lowering of LDL-C (Table 6).1 Mechanism of action. Cholesterol absorption inhibitors selectively inhibit the absorption of cholesterol from the small intestine, resulting in a reduced delivery of cholesterol to the liver and decreased hepatic cholesterol stores, thereby lowering cholesterol levels, primarily LDL-C.1 Dosing and administration. The initial and maintenance dose is 10 mg daily, in conjunction with a statin

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or bile acid sequestrants. Tablets can be taken with or without food.1 Precautions and contraindications. Ezetimibe is listed as pregnancy category C and should be avoided to reduce risks. Caution should be used in patients with hepatic dysfunction.1 Adverse effects. Ezetimibe is generally well tolerated and has very few adverse effects. The most common complaints include GI disorders, such as diarrhea and abdominal pain, as well as back pain, arthralgia, and sinusitis.1 Drug interactions. Bile acid sequestrants may hinder absorption of ezetimibe. Therefore, ezetimibe should be administered 1 hour before or 4 hours after the bile acid sequestrant, if it is used concomitantly. Fibrates can increase cholesterol excretion into the bile; therefore, concurrent use is not advised.1 Monitoring. A baseline lipid profile and liver function tests should be performed before initiating therapy.

When ezetimibe is used in combination with a statin, liver enzymes should be monitored before initiating statin therapy, every 3 months in the first 6 months of treatment and periodically thereafter. An international normalized ratio (INR) should also be monitored in patients taking warfarin.1

Fibrates The primary lipid-lowering effect of fibrates is on triglyceride levels. Fibrates also have an additional effect of increasing HDL-C level (Table 7).1 Mechanism of action. The manner in which fibrates exert their lipid-lowering effect is unclear. However, these agents can increase lipoprotein lipase, thereby breaking down VLDL. Fibrates also decrease hepatic VLDL synthesis while enhancing the removal of triglyceride-rich lipoproteins.1 Dosing and administration. Fibrates are generally dosed once to twice daily, often 30 minutes before a meal or with a meal. Lower doses are initiated and can be titrated up every 1 to 2 months, as warranted, to achieve the optimal or maximum dose.1 Precautions and contraindications. Fibrates are listed as pregnancy category C and should be avoided to

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reduce risks. Caution and lower doses should be used in the elderly and patients with renal dysfunction.1 Preexisting gallbladder disease, hepatic dysfunction, and severe renal dysfunction are contraindications for fibrate use.1 Adverse effects. Fibrates are generally well tolerated and have very few adverse effects. The most common complaints are GI, including indigestion, nausea, diarrhea, flatulence, and abdominal pain. Rare adverse effects include rash, fever, weight gain, muscle weakness, drowsiness, decreased potassium levels, anemia, and low white blood cell count.1 Drug interactions. Fibrates are highly protein bound and can increase the adverse effects of medications that are also highly protein bound, such as warfarin, sulfonylureas, and meglitinides.1 Monitoring. Triglycerides and cholesterol levels should be measured before initiating fibrate therapy and at 3- to 6-month intervals. Liver function tests and a

complete blood cell count should also be evaluated at baseline and 6-month intervals. Fibrate therapy should be discontinued when liver enzymes are >3 times the upper limit of normal.1 Hematologic changes, such as decreased hemoglobin and hematocrit, thrombocytopenia, and neutropenia, should be monitored. If fibrates are to be used concurrently with statins, sulfonylureas, warfarin, or bile acid sequestrants, close monitoring is warranted to decrease the risks of hypoglycemia and increased INR.1

Niacin The primary effect of niacin is an increase in HDL-C, with a small decrease in triglyceride levels and LDL-C. Although niacin increases HDL-C levels, it can also increase blood glucose levels, especially in patients with prediabetes and in those with newly diagnosed diabetes (Table 8).1 Mechanism of action. Niacin reduces the catabolism

Table 7 Lipid-Lowering Comparison of Fibrates

Drug (brand) Fenofibrate(Tricor)

Total cholesterol change from LDL-C change TG change from HDL-C change baseline, % from baseline, % baseline, % from baseline, %

Daily dose, cost 145 mg, $5.59

Gemfibrozil(Lopid) 600 mg bid, $0.38

–18

–20

–29

11

–10

±10

–20 to –50

10-15

HDL-C indicates high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride.

Sources: Reference 1; www.drugstore.com.

Table 8 Lipid-Lowering Effects of Niacin

Drug (brand)

Daily dose, cost

Total cholesterol, change from LDL-C, change TG, change from HDL-C, change baseline, % from baseline, % baseline, % from baseline, %

Niacin 1000 mg, $0.11

N/A

–6

N/A

N/A

1500 mg, $0.11

N/A

–12

N/A

N/A

2000 mg, $0.11

N/A

–16

N/A

N/A

500 mg, $2.93

–2

–3

–5

10

1000 mg, $4.99

–5

–9

–11

15

1500 mg, $7.80

–11

–14

–28

22

2000 mg, $9.99

–12

–17

–35

26

Extended-release niacin (Niaspan)

HDL-C indicates high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; N/A, not available; TG, triglyceride.

Sources: Reference 1; www.drugstore.com.

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Table 9 Lipid-Lowering Effect of Omega-3 Fatty Acid

Drug (brand)

Total cholesterol, change from LDL-C change TG, change from HDL-C, change Daily dose, cost baseline, % from baseline, % baseline, % from baseline, %

Omega-3 fatty acid (Omacor) 1 g, $1.57

N/A

10

â&#x20AC;&#x201C;3.5

13

2 g, $1.57

N/A

31

â&#x20AC;&#x201C;45

13

HDL-C indicates high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; N/A, not available; TG, triglyceride.

Sources: Reference 1; www.drugstore.com.

of HDL-C and selectively decreases the excretion of HDL-C. In addition, niacin reduces hepatic VLDL-C production, which results in a decrease of LDL-C and triglyceride levels.1 Dosing and administration. Niacin is available in immediate-release, sustained-release, and extendedrelease formulations and should not be interchanged.

Immediate-release niacin is preferred over sustainedrelease niacin, because of unfavorable adverse effects.1 For immediate-release niacin, doses as low as 100 mg 3 times daily can be gradually titrated to 3 g daily in divided doses. For sustained-release niacin, doses as low as 250 mg twice daily can be titrated to 2 g daily in a single or divided dose. Niacin should be taken 30 minutes after an aspirin or with a low-fat snack to minimize flushing effects. Niacin should not be taken with hot beverages or with alcohol.1 Precautions and contraindications. Niacin is listed as pregnancy category C and should be avoided during pregnancy. Caution should be used in patients with preexisting gout, a history of heavy alcohol use, or renal dysfunction. Liver dysfunction, active peptic ulcer disease, and arterial bleeding are contraindications.1 Adverse effects. The most common complaints are headache, hypotension, and GI discomfort, such as nausea, vomiting, diarrhea, flushing, pruritus, and rash.

Flushing usually dissipates with continuous use and can be reduced by taking niacin with meals. Aspirin taken once daily 30 minutes before the niacin dose can also minimize flushing. Patients taking >2 g of niacin daily may be at risk for hepatotoxic effects. Treatment should be discontinued when liver enzymes are >3 times the upper limit of normal.1 Drug interactions. Alcohol and hot drinks can increase the flushing and pruritus adverse effects.

Rhabdomyolysis may occur when used in combination with statins.1 Monitoring. A baseline lipid profile, liver function, uric acid, and blood glucose levels should be performed

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before initiating niacin therapy and repeated at 6-week intervals while adjusting the dose. Lipid profiles should be reviewed at 3- to 6-month intervals. Blood glucose levels should be monitored regularly, especially in those with newly diagnosed diabetes or with prediabetes. Liver enzymes should also be monitored at 3-month intervals during the first year of treatment.1

Omega-3 Fatty Acids Lowering triglyceride levels is the primary effect of omega-3 fatty acids (Table 9). Increased HDL-C level is a secondary benefit, but this occurs only when high doses are used. LDL-C levels tend to increase, which is dose related.1 Mechanism of action. Omega-3 fatty acids exert their effect by reducing hepatic VLDL-C production. They also reduce the quantity of free fatty acids available for triglyceride synthesis, thereby lowering VLDL-C synthesis and increasing lipoprotein lipase activity, resulting in triglyceride clearance.1 Dosing and administration. The initial dose of omega-3 fatty acids is one to two 1000-mg capsules daily and can be titrated up to a maximum dose of 4 g daily.

Omega-3 fatty acid should be taken with food to minimize GI adverse effects.1 Precautions and contraindications. There are no adequate studies in pregnant women; therefore, omega-3 fatty acids should be avoided during pregnancy. Caution should be used in patients with renal or hepatic dysfunction, the elderly, and those at high risk for hemorrhage.1 Adverse effects. The most common adverse effects are dizziness and GI discomfort, such as dyspepsia, nausea, and abdominal pain. Rare adverse effects include headache, pruritus, and hyperglycemia.1 Drug interactions. Omega-3 fatty acids may decrease the production of thromboxane A2, resulting in an increase in bleeding time. Omega-3 fatty acids taken in combination with warfarin therapy can increase the INR.1

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Table 10 Clinical Trials Using Statin Therapy

See print issue.

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Monitoring. A baseline lipid profile and liver function tests should be performed before initiating omega-3 fatty acid therapy and repeated at regular intervals, while adjusting dosage. Patients taking warfarin should have their INR monitored for increases in bleeding time.1 Table 10 (available in the print issue only) displays the results of 7 major clinical trials using statin treatment, which specifies the type and dose of statin used, the baseline LDL-C, the number of patients with diabetes versus the total number of participants, CVD outcome, and relative risk reduction for patients with diabetes versus those without.

Relative risk reduction determines an appropriate treatment plan, by accounting not only for the effectiveness of a proposed treatment but also for the relative likelihood of an incident (positive or negative) occurring in the absence of treatment.

The clinical trials are further divided by primary and secondary prevention. Primary prevention involves preventing risk factors that lead to chronic diseases, infections, and injuries. Secondary prevention is aimed to prevent further exacerbation of a known problem.

Conclusion Becoming familiar with lipid treatment goals and the many therapies available today can help providers and payers implement the appropriate approach to the management of the risk factors associated with diabetic dyslipidemia and reduce the burden of this disease.

Treatment goals and strategies for diabetic dyslipidemia must be given equal importance and must be as aggressive as those developed for hyperglycemia. The primary lipoprotein target is LDL-C; however, triglycerides, HDL-C, and particle size of LDL-C must be addressed in the treatment plan. The goal of initiating drug therapy is to achieve optimal levels of these lipoproteins.

Combinations of lipid-lowering agents are often warrant-

ed to achieve this goal. Adding medications to existing regimens requires patients to change their behavior.

Therefore, the patient’s readiness for change and the level of conviction and confidence must be evaluated.

The use of precombined medications can be beneficial for patients who are not willing to take more medications. Statins are traditionally the first medication of choice in diabetic dyslipidemia. However, the addition of a cholesterol absorption inhibitor (eg, ezetimibe) can enhance lowering of LDL-C, and fibrates can reduce triglyceride levels and raise HDL-C levels. Two or more lipid-lowering medications may be necessary for some patients. Lipid profiles, liver enzymes, and adverse effects, as well as patient adherence must be routinely monitored. Lipid management may be challenging at times in patients with diabetes, but educating patients and getting them involved in the treatment plan may lead to more productive results. ■ Author Disclosure Statement Dr Daniel reported no conflicts of interest.

References 1. Cornell S, Vito CJ. Pharmacologic therapies: dyslipidemia and hypertension in persons with diabetes. In: Mensing C, ed. The Art and Science of Diabetes SelfManagement Education: A Desk Reference for Healthcare Professionals. Chicago, IL: American Association of Diabetes Educators; 2006:399-412.

2. Inzucchi S, Amatruda J. Lipid management in patients with diabetes: translating guidelines into action. Diabetes Care. 2003;26:1309-1311.

3. Solano M, Goldberg R. Lipid management in type 2 diabetes. Clin Diabetes. 2006; 24:27-32.

4. Haffner SM, for the American Diabetes Association. Dyslipidemia management in adults with diabetes. Diabetes Care. 2004;27(suppl 1):S68-S71.

5. Centers for Disease Control and Prevention. Diabetes: successes and opportunities for population-based prevention and control. At a glance, 2011. www.cdc.gov/ chronicdisease/resources/publications/AAG/ddt.htm. Accessed June 20, 2011.

6. National Cholesterol Education Program. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III): Final Report. NIH Publication No. 02-5215. September 2002. www.nhlbi.nih.gov/guide lines/cholesterol/atp3full.pdf. Accessed June 20, 2011.

7. Wilson PWF, D’Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837-1847.

8. US Food and Drug Administration. FDA drug safety communication: new restrictions, contraindications, and dose limitations for Zocor (simvastatin) to reduce the risk of muscle injury. June 8, 2011. www.fda.gov/Drugs/DrugSafety/ucm256581.htm.

Accessed June 20, 2011.

STAKEHOLDER PERSPECTIVE The Time Is Now to Promote Aggressive Lipid Management to Prevent Macrovascular Complications in Patients with Type 2 Diabetes MEDICAL DIRECTORS: Type 2 diabetes is a major area of concern for health plans. With the rising tide of obesity in the United States, we are set to experience an unprecedented portion of the population who will develop type 2 diabetes, in particular among the elderly. The cost of caring for the diabetic patient

is largely driven by the complications of the disease. In this article by Dr Daniel, we are reminded that control of hemoglobin (Hb) A1c is only part of the diabetic story. Although good control of HbA1c will help prevent microvascular complications of the disease, macrovascular complications are largely unaffected by Continued

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STAKEHOLDER PERSPECTIVE (Continued) such tight control. We are further reminded by Dr Daniel that management of lipid disorders, especially the management of low-density lipoprotein cholesterol (LDL-C) levels, will ultimately produce improvement in or prevent potential macrovascular complications of diabetes, such as myocardial infarction and stroke.

Therefore, the focus of health plans on the management of diabetes and its associated complications must go beyond the reduction of HbA1c levels. At a minimum, diabetic management programs need to include lifestyle modifications, weight management programs, exercise counseling, disease education, and medication adherence programs. Drug therapy to lower LDL-C levels is one of the cornerstone treatments for the management of the diabetic patient. Health plans must promote aggressive lipid management in a cost-effective manner to help patients reduce their risk for atherosclerotic complications of the disease.

With the impending introduction of new generic options among the statin class of drugs, now is the time for health plans to look at their management strategies regarding this therapeutic class and their benefit

design. The promotion of aggressive lipid management will become more cost-effective with the availability in the near future of generic atorvastatin, which will allow diabetic members to have access to a low-cost, highpotency statin therapy.

Health plans must act now to take advantage of this opportunity and simultaneously help improve outcomes for this ever-growing group of patients.

PATIENTS: In addition to managing blood glucose and HbA1c, physicians must continue to educate diabetic patients about how to manage the risk for macrovascular complications associated with their disease. To accomplish this, diabetic patients must be informed about the importance of blood pressure management and the importance of adhering to cholesterol-lowering medication therapy for the prevention of diabetes complications seen in individuals whose lipid profile is not properly managed.

Gary M. Owens, MD President, Gary Owens Associates Philadelphia, PA

CALL FOR PAPERS American Health & Drug Benefits offers an open forum for all healthcare participants to exchange ideas and present their data, innovations, and initiatives to facilitate patient-centered healthcare and benefit design models that meet the needs of all stakeholders—Distributors, Employers, Evaluators, Manufacturers, Patients, Payers, Providers, Purchasers, Regulators, and Researchers.

Readers are invited to submit articles that aim at improving the quality of patient care and patient well-being, the health of communities and patient populations, as well as other topics relevant to benefit design with specific implications to policymakers, payers, and employers.

Areas of High Interest Include: • Adherence Concerns • Benefit Design • Case Studies • Comparative Effectiveness Research • Cost Analyses • Decision-Making Tools • Ethics in Medicine

• Health Economics Research • Health Plan Initiatives • Health Information Technology • Industry Trends • Innovations in Healthcare • Literature Reviews • Medicare/Medicaid

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Submit articles to editorial@AHDBonline.com. For more information call 732-992-1536.

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