September 2012, VOL 1, NO 4 by The Oncology Nurse

The official publication of

September 2012 Volume 1 • Number 4 A Peer-Reviewed Journal

PM O

PERSONALIZED MEDICINE IN ONCOLOGY TM

INTERVIEW WITH THE INNOVATORS Novel Approaches to Delivering Personalized Medicine: An Interview With Thomas C. Reynolds, MD, PhD.. ..................Page 30

CLINICAL TRIAL DESIGN Adaptive Clinical Trial Design: From Simple Dose-Finding Trials to Large-Scale Personalized Medicine Trials .............................................Page 36

MYELODYSPLASTIC SYNDROME Personalized Therapy in the Management of Myelodysplastic Syndrome... ........................Page 49

PHARMACOGENOMICS Pharmacogenomics in Cancer Care: Adding Some Science to the Art of Medicine.... ........Page 56

ALSO IN THIS ISSUE… • Progress in Treating Prostate Cancer............Page 19 • Targeted Drug Leads to Marked Responses in NSCLC...................................................Page 23

IMPLEMENTING THE PROMISE OF PROGNOSTIC PRECISION INTO PERSONALIZED CANCER CARE

In partnership with

Linker Antibody Specific for a tumor-associated antigen that has restricted expression on normal cells.4,8

Cytotoxic agent Designed to kill target cells when internalized and released.4,8

Attaches the cytotoxic agent to the antibody. Newer linker systems are designed to be stable in circulation and release the cytotoxic agent inside targeted cells.4,8,9

he Global Biomarkers Consortium™ (GBC) is a community of worldrenowned healthcare professionals who will convene in multiple educational forums in order to better understand the clinical application of predictive molecular biomarkers and advanced personalized care for patients.

PM O

September 2012 Volume 1 • Number 4

PERSONALIZED MEDICINE IN ONCOLOGY ™

CONFERENCE NEWS News Briefs

PAGE 13

Surgery Versus Observation for Localized Prostate Cancer Team Approach Enhances Choice of Observation in Men With Low-Risk Prostate Cancer

Save the date for the Second Annual Conference, October 4-6, 2013 Visit www.globalbiomarkersconsortium.com to register

Professional Experience of GBC Attendees 56.7%

26.7%

6.7% 3.3% 6.7%

Blood Test for Ovarian Cancer Weightlifting in Women at Risk for Breast Cancer–Related Lymphedema

Severe Diarrhea Associated With Molecularly Targeted Agents Can Impact Quality of Life and Healthcare Resource Utilization

PAGE 17

Risk of Cardiotoxicity With Targeted Therapies Exaggerated

PAGE 18

Progress in Treating Prostate Cancer

PAGE 19

Mucositis Management to Become More Personalized

PAGE 21

Targeted Drug Leads to Marked Responses in NSCLC

PAGE 23

Progressive Myeloma Responds to Monoclonal Antibody

PAGE 24

New Approach for Predicting Treatment-Related Side Effects

PAGE 26

1-3 years

INTERVIEW WITH THE INNOVATORS

3-5 years

Novel Approaches to Delivering Personalized Medicine: An Interview With Thomas C. Reynolds, MD, PhD

5-10 years 10-20 years >20 years

Older Patients With Mantle Cell Lymphoma

Volume 1 • No 4

PAGE 30

PMO speaks with the Chief Medical Officer of Seattle Genetics to discuss their approach to personalized medicine.

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Image: Colored scanning electron micrograph (SEM) of a lung cancer cell.

One focus: a shared commitment to improve the lives of cancer patients everywhere. Millennium: The Takeda Oncology Company is developing an extensive pipeline — among the top in oncology worldwide — with more than 17 compounds in development for a broad range of solid and hematological cancers. Our pipeline — rich in novel compounds — includes multiple candidates that target seven disease pathways: protein homeostasis, anti-angiogenesis, growth-signaling inhibition, cell-cycle inhibition, apoptosis, immunomodulators and hormone regulation. To make a dramatic impact on cancer therapeutics, we are dedicated to a strong partnership with the oncology community.

PUBLISHING STAFF SENIOR VICE PRESIDENT, SALES AND MARKETING Philip Pawelko phil@greenhill.com PUBLISHERS John W. Hennessy john@greenhillhc.com Russell Hennessy russell@greenhillhc.com DIRECTOR, CLIENT SERVICES Lou Lesperance Jr lou@greenhillhc.com MANAGING DIRECTOR Pam Rattananont Ferris

Adaptive Clinical Trial Design: From Simple Dose-Finding Trials to Large-Scale Personalized PAGE 36 Medicine Trials

STRATEGIC EDITOR Robert E. Henry SENIOR COPY EDITOR BJ Hansen PRODUCTION MANAGER Marie RS Borrelli QUALITY CONTROL DIRECTOR Barbara Marino BUSINESS MANAGER Blanche Marchitto

Fei YE, PhD; Yu Shyr, PhD Use of adaptive trial designs for drug development trial designs saves resources and/or improves the efficiency and effectiveness of clinical trials while minimizing all potential sources of bias in an adaptive trial.

MYELODYSPLASTIC SYNDROME

CIRCULATION DEPARTMENT circulation@greenhillhc.com Personalized Medicine in Oncology, ISSN 2166-0166 (print); ISSN applied for (online) is published 6 times a year by Green Hill Healthcare Communications, LLC, 1249 South River Road, Suite 202A, Cranbury, NJ 08512. Telephone: 732.656.7935. Fax: 732.656.7938. Copyright ©2012 by Green Hill Healthcare Communications, LLC. All rights reserved. Personalized Medicine in Oncology logo is a trademark of Green Hill 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. Printed in the United States of America. EDITORIAL CORRESPONDENCE should be addressed to EDITORIAL DIRECTOR, Personalized Medicine in Oncology (PMO), 1249 South River Road, Suite 202A, Cranbury, NJ 08512. YEARLY SUBSCRIPTION RATES: United States and possessions: individuals, $50.00; institutions, $90.00; single issues, $5.00. Orders will be billed at individual rate until proof of status is confirmed. Prices are subject to change without notice. Correspondence regarding permission to reprint all or part of any article published in this journal should be addressed to REPRINT PERMISSIONS DEPARTMENT, Green Hill Healthcare Communications, LLC, 1249 South River Road, Suite 202A, Cranbury, NJ 08512. The ideas and opinions expressed in PMO do not necessarily reflect those of the editorial board, the editorial director, or the publishers. Publication of an advertisement or other product mention in PMO should not be construed as an endorsement of the product or the manufacturer’s claims. Readers are encouraged to contact the manufacturer with questions about the features or limitations of the products mentioned. Neither the editorial board nor the publishers assume any responsibility for any injury and/or damage to persons or property arising out of or related to any use of the material contained in this periodical. The reader is advised to check the appropriate medical literature and the product information currently provided by the manufacturer of each drug to be administered to verify the dosage, the method and duration of administration, or contraindications. It is the responsibility of the treating physician or other healthcare professional, relying on independent experience and knowledge of the patient, to determine drug dosages and the best treatment for the patient. Every effort has been made to check generic and trade names, and to verify dosages. The ultimate responsibility, however, lies with the prescribing physician. Please convey any errors to the editorial director.

Volume 1 • No 4

PERSONALIZED MEDICINE IN ONCOLOGY ™

CLINCIAL TRIAL DESIGN

EDITORIAL DIRECTOR Kristin Siyahian kristin@greenhillhc.com

PM O

Personalized Therapy in the Management of Myelodysplastic Syndrome

PAGE 49

A report from the 2012 conference of the Global Biomarkers Consortium.

PHARMACOGENOMICS Pharmacogenomics in Cancer Care: Adding Some Science to the Art of Medicine

PAGE 56

Navin Pinto, MD; Mark J. Ratain, MD Three hypothetical case scenarios illustrate the power of prospective genotyping in providing personalized approaches to therapy.

OUR MISSION The mission of Personalized Medicine in Oncology is to deliver practice-changing information to clinicians about customizing healthcare based on molecular profiling technologies, each patient’s unique genetic blueprint, and their specific, individual psychosocial profile, preferences, and circumstances relevant to the process of care. OUR VISION Our vision is to transform the current medical model into a new model of personalized care, where decisions and practices are tailored for the individual – beginning with an incremental integration of personalized techniques into the conventional practice paradigm currently in place.

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Eliminate the ambiguity in genomic test results. SYMPHONY™delivers 100% definitive results – every time. Here’s why: All 25,000 genes in human genome analyzed All 7 metastatic pathways included

Over 10,000 patients tested Validated in 25 clinical studies The result is SYMPHONY – the only molecular diagnostic suite that can give you

100% definitive results for breast cancer tumor profiling.

Visit agendia.com or call 1-888-321-2732 today.

Breast Cancer Recurrence Signature Molecular Subtyping Signature ER/PR/HER2 Expression Assay

Therapy Gene Assay

Now Availible in ParAffIn 22 Morgan | Irvine | CA 92618 | p: 888.321.2732 | f: 866.756.7548 customercare@agendia.com | www.agendia.com ©Copyright 2012 Agendia. All rights reserved. Agendia, MammaPrint, TargetPrint and TheraPrint are registered trademarks of Agendia. BluePrint and SYMPHONY are trademarks of Agendia.

Editorial Board Editor in Chief AL B. BENSON III, MD Northwestern University Chicago, Illinois

SECTION EDITORS Breast Cancer EDITH PEREZ, MD Mayo Clinic Jacksonville, Florida

Gastrointestinal Cancer EUNICE KWAK, MD Massachusetts General Hospital Cancer Center Harvard Medical School Boston, Massachusetts

Drug Development IGOR PUZANOV, MD Vanderbilt University Vanderbilt-Ingram Cancer Center Nashville, Tennessee

Hematologic Malignancies GAUTAM BORTHAKUR, MD The University of Texas MD Anderson Cancer Center Houston, Texas

Lung Cancer VINCENT A. MILLER, MD Foundation Medicine Cambridge, Massachusetts

Pathology DAVID L. RIMM, MD, PHD Yale Pathology Tissue Services Yale University School of Medicine New Haven, Connecticut

Melanoma DOUG SCHWARTZENTRUBER, MD Indiana University Simon Cancer Center Indianapolis, Indiana

Predictive Modeling MICHAEL KATTAN, PHD Case Western Reserve University Cleveland, Ohio

Prostate Cancer OLIVER SARTOR, MD Tulane University New Orleans, Louisiana

EDITORIAL BOARD

TONY ALBINO, PHD Signal Genetics LLC New York, New York GREGORY D. AYERS, MS Vanderbilt University School of Medicine Nashville, Tennessee LYUDMILA BAZHENOVA, MD University of California, San Diego San Diego, California LEIF BERGSAGEL, MD Mayo Clinic Scottsdale, Arizona

HOPE S. RUGO, MD University of California, San Francisco San Francisco, California

K. PETER HIRTH, PHD Plexxikon, Inc. Berkeley, California

DANIELLE SCELFO, MHSA Genomic Health Redwood City, California

HOWARD L. KAUFMAN, MD Rush University Chicago, Illinois

LEE SCHWARTZBERG, MD The West Clinic Memphis, Tennessee

KATIE KELLEY, MD UCSF School of Medicine San Francisco, California

JOHN SHAUGHNESSY, PHD University of Arkansas for Medical Sciences Little Rock, Arkansas

MINETTA LIU, MD Georgetown University Hospital Washington, DC

KENNETH BLOOM, MD Clarient Inc. Aliso Viejo, California

KIM MARGOLIN, MD University of Washington Fred Hutchinson Cancer Research Center Seattle, Washington

MARK S. BOGUSKI, MD, PHD Harvard Medical School Boston, Massachusetts GILBERTO CASTRO, MD Instituto do Câncer do Estado de São Paulo São Paulo, Brazil MADELEINE DUVIC, MD The University of Texas MD Anderson Cancer Center Houston, Texas BETH FAIMAN, PHD(C), MSN, APRN-BC, AOCN Cleveland Clinic Taussig Cancer Center Cleveland, Ohio STEPHEN GATELY, MD TGen Drug Development (TD2) Scottsdale, Arizona

STEVEN T. ROSEN, MD, FACP Northwestern University Chicago, Illinois

STEVEN D. GORE, MD The Johns Hopkins University School of Medicine Baltimore, Maryland

SANJIV S. AGARWALA, MD St. Luke’s Hospital Bethlehem, Pennsylvania

GENE MORSE, PHARMD University at Buffalo Buffalo, New York AFSANEH MOTAMED-KHORASANI, PHD Radient Pharmaceuticals Tustin, California NIKHIL C. MUNSHI, MD Dana-Farber Cancer Institute Boston, Massachusetts

Volume 1 • No 4

STEVEN O’DAY, MD John Wayne Cancer Institute Santa Monica, California

DARREN SIGAL, MD Scripps Clinic Medical Group San Diego, California DAVID SPIGEL, MD Sarah Cannon Research Institute Nashville, Tennessee

SHEILA D. WALCOFF, JD Goldbug Strategies, LLC Rockville, Maryland

DAVID A. PROIA, PHD Synta Pharmaceuticals Lexington, Massachusetts

PERSONALIZED MEDICINE

JAMIE SHUTTER, MD South Beach Medical Consultants, LLC Miami Beach, Florida

MOSHE TALPAZ, MD University of Michigan Medical Center Ann Arbor, Michigan

ANAS YOUNES, MD The University of Texas MD Anderson Cancer Center Houston, Texas

RAFAEL ROSELL, MD, PHD Catalan Institute of Oncology Barcelona, Spain

LAWRENCE N. SHULMAN, MD Dana-Farber Cancer Institute Boston, Massachusetts

ONCOLOGY

September 2012

MAY 2-5, 2013

THIRD ANNUAL CONFERENCE

Influencing the Patient-Impact Factor May 2-5, 2013 Westin Diplomat Hollywood, Florida

For more information please visit

www.AVBCConline.org

Letter From the Board

PMO: Identifying the Possibilities of Personalized Medicine

elcome to this issue of Personalized Medicine in Oncology (PMO), the official publication of Global Biomarkers Consortium. I want to offer to you a simple insight into what PMO can mean to you in your practice. It centers on the importance of integrating targeted biologicals into practice. Winning the war on cancer depends on the intelligent clinical execution of personalized medicine. Acceptance of biologicals, the prize weapon in personalized medicine’s arsenal, requires responsible, value-based implementation. This requires a working knowledge of the governing dynamics of personalized medicine in general and biologicals in particular. Enter Personalized Medicine in Oncology. Formed under the guidance of leading Lawrence N. oncologists and hematologists, PMO cultivates clinical acumen in personalized Shulman, MD medicine. Our method: identify the possibilities of personalized medicine to impact on cancer, frame clinicians’ expectations, provide a balanced understanding of personalized medicine techniques, and provide a special emphasis on biologicals and the pathophysiology of cancers. The net effect is to transform biologicals from an academic curiosity into a trusted therapeutic tool, its value understood, measurable, and affordable through their skillful use. The net result of this editorial mission leads to our Editorial Vision Statement: an oncology healthcare environment receptive to personalized medicine innovation, based on clinicians’ practical knowledge of the value it delivers. We are delighted to have you as part of our reading community and would like to invite you to join us for the 2nd Annual Conference of the Global Biomarkers Consortium on October 4-6, 2013, in Boston, Massachusetts. The conference will educate physicians specializing in hematology/oncology, pathology, and genetics on the state-of-the-art advances in the understanding of tumor biomarkers and their use in the clinical management of a variety of solid tumors and hematologic malignancies. To learn more and to register for this conference, please visit www.globalbiomarkersconsortium.com.

Sincerely,

Lawrence N. Shulman, MD Dana-Farber Cancer Institute PMO Editorial Board Member

Volume 1 • No 4

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

From the Editorial Director

Introducing PMO Dear Reader,

t is with great pleasure and excitement that I introduce Personalized Medicine in Oncology (PMO) to the community of oncology clinicians. Our goal is to sensitize practitioners to the performance realities of new diagnostic and treatment discoveries and to clarify molecular profiling technologies as they relate to diagnostic, prognostic, and predictive medicine. PMO will feature diagnostic and clinical treatment information concerning these three root aspects of personalized medicine in oncology. We also seek to expand the process of combining scientific aspects of personalKristin Siyahian ized medicine with a highly personalized, psychosocial rapport among patient, caregiver, and physician, factoring all environmental dynamics into each patient’s treatment regimen. Finally, we intend to cultivate the practicing oncologist’s ability to distinguish personalized medicine innovation value from novelty based on knowledge of the biological basis of pathophysiology and the pharmacodynamics of biological treatments. On behalf of our editorial board and staff, I’d like to welcome you to our reading community.

With best regards,

Kristin Siyahian Editorial Director

Volume 1 • No 4

WWW.PERSONALIZEDMEDONC.COM

September 2012

PMPM O C

ERSONALIZED EDICINE IN ONCOLOGY

ALL FOR PAPERS

Personalized Medicine in Oncology’s mission is to deliver practice-changing information to clinicians about customizing healthcare based on molecular profiling technologies and each patient’s unique genetic blueprint. Our vision is to transform the old medical model of stratified medicine into a new model of personalized care where all decisions and practices are tailored to the individual. The goal of Personalized Medicine in Oncology is to sensitize practitioners to the performance realities of new diagnostic and treatment discoveries and to clarify molecular profiling technologies as they relate to diagnostic, prognostic, and predictive medicine. PMO will feature diagnostic and clinical treatment information concerning these 3 root aspects of personalized medicine in oncology. Readers are invited to submit articles for consideration in the following categories:

Biologicals in Trial •

Exploring the challenges of clinical trial design and patient enrollment

•

Presentation of emerging clinical data

Genetic Profiling Technologies •

What technologies are available to clinicians and consumers and their impact on diagnostic, prognostic, and predictive medicine

In Practice Predictive Models and Diagnostics •

Genetics and Biomarkers •

•

A practical guide for community-based oncologists discussing clinical applications and strategies for incorporating personalized medicine techniques into practice

•

Development of treatment algorithms

A look at available diagnostic technologies and implementation in the community practice setting

Exploring genetic discoveries and impact on predictors of disease and therapeutic response

The Cost of Personalized Medicine •

Personalized medicine policy drivers

•

Payer coverage of diagnostics and biologics

N=1 •

Case studies, patient-reported outcomes, defining treatment goals, partnering with patients and caregivers

Submit the entire manuscript and a cover letter stating the objectives of the article to PMO@greenhillhc.com. Manuscripts should follow the Author Guidelines available at www.PersonalizedMedOnc.com. "

News Briefs

Surgery Versus Observation for Localized Prostate Cancer Alice Goodman or men with localized prostate cancer detected by prostate-specific antigen (PSA) level, treatment with radical prostatectomy did not significantly reduce mortality compared with observation, according to overall results of the large, randomized, controlled PIVOT trial (Wilt TJ, et al. N Engl J Med. 2012; 367:203-213). All-cause mortality and prostate-specific mortality were similar for the surgery and observation groups over a 12-year follow-up. Results suggest that surgery may be a better option than observation for men with intermediate- and high-risk localized prostate cancer, but low-risk localized prostate cancer can be safely managed with observation. Overall, absolute differences in mortality favoring surgery were less than 3 percentage points, explained lead author Timothy J. Wilt, MD, Minneapolis Veterans Affairs Health Care System, Minnesota. “Surgery might reduce mortality for men with higher PSA values and possibly among men with higher-risk tumors, but not among men with PSA levels of ≤10 ng/mL or low-risk tumors,” Wilt wrote. He noted that PIVOT was conducted in the early era of PSA testing, and that in the current era men suspected of having prostate cancer undergo repeated PSA testing and sometimes repeat biopsies, which detect more indolent cancers. These factors increase the likelihood of overdiagnosis and overtreatment. “Our findings support observation for men with localized prostate cancer, especially those who have low-risk disease,” he wrote. PIVOT randomized 364 men to radical prostatectomy and 367 to observation alone. All participants were suspected of having prostate cancer based on PSA testing and had histologically confirmed localized prostate cancer diagnosed within the previous year. Mean age was 67 years, about one-third were black, and median PSA value was 7.8 ng/mL. About 40% of the men had low-risk prostate cancer, 34% intermediaterisk prostate cancer, and 21% high-risk prostate cancer.

Volume 1 • No 4

At a median follow-up of 10 years, mortality was 47% in the surgery group versus 49.9% in the observation group, an absolute reduction of 2.9% for surgery. The rates of prostate-specific mortality were 5.8% for surgery versus 8.4% for observation, an absolute risk reduction of 2.6%. The effect of treatment on all-cause mortality was similar according to age, race, coexisting illness, performance status, or histologic tumor features. Radical prostatectomy was associated with reduced all-cause mortality among men with PSA >10 ng/mL and for men with intermediate- or high-risk tumors. Perioperative adverse events (occurring within 30 days of surgery) were reported in 21.4% of men. Rates of urinary incontinence and erectile dysfunction were significantly higher in the radical prostatectomy group (P<.001 for both comparisons vs observation). u

At a median follow-up of 10 years, mortality was 47% in the surgery group versus 49.9% in the observation group, an absolute reduction of 2.9% for surgery. Team Approach Enhances Choice of Observation in Men With Low-Risk Prostate Cancer

en diagnosed with low-risk prostate cancer are more likely to choose active surveillance as their primary treatment if their care is managed by a multidisciplinary team, according to a recent study published online ahead of print July 30, 2012, in the Journal of Clinical Oncology. In 2012, about 240,000 men in the United States will be diagnosed with prostate cancer. About 70% will be low risk, but more than 90% of these men will opt for definitive treatment with radiation or radical prostatectomy. Neither of these treatments is superior to active surveillance in reducing prostate cancer–specific mortality. Active surveillance entails observation with monitoring for disease progression and initiating curative therapy at the earliest sign of progression.

WWW.PERSONALIZEDMEDONC.COM

September 2012

News Briefs

“Efforts to prevent unnecessary treatment are crucial from medical, social, and economic standpoints,” wrote the authors. Multidisciplinary teams provide a balanced view of the risks and benefits of various treatment options, while a single specialist tends to recommend the treatment he or she is trained to deliver, the investigators wrote. Lead author Jason Efstathiou, MD, Massachusetts General Hospital, Boston, and colleagues analyzed choices made by 701 men with low-risk prostate cancer who were treated at 3 different Boston area hospitals. Low risk was defined as Gleason score of 6 or less, PSA level of 10 ng/mL or less, and clinical stage T1c or T2a. At baseline, the groups were similar for age, comorbidity score, family history of prostate cancer, race, marital status, and annual income.

The long-term prognosis is poor for older patients with mantle cell lymphoma. Treatment with chemotherapy achieves low rates of complete remission.

One-third were managed by a multidisciplinary team of doctors (urologic, radiologic, and medical oncologists), and 43% of this group opted for active surveillance rather than surgery or radiation. By contrast, only 22% of men seen by individual practitioners opted for active surveillance. The proportion of men treated with radiation or prostatectomy declined by about 30% in the active surveillance group. In a multivariate analysis, older age, being unmarried, increased comorbidities, fewer positive cores on biopsy, and consultation with a multidisciplinary team were significantly associated with choice of active surveillance. Efstathiou commented that a visit to a multidisciplinary clinic allowed the patient to hear multiple views about appropriate management choices and for improved informed decision making. He said this was the first study to show that multidisciplinary care may reduce bias of specialists toward the type of care they deliver. u —AG

Volume 1 • No 4

Older Patients With Mantle Cell Lymphoma

-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) induction therapy followed by maintenance therapy with rituximab was more effective than R-FC (rituximab, fludarabine, and cyclophosphamide) followed by maintenance therapy with interferon alfa in older patients with mantle cell lymphoma, according to a recently published prospective, randomized, double-blind clinical trial (Kluin-Nelemans HC, et al. N Engl J Med. 2012;367:520-531). “The excellent results with rituximab administered as maintenance therapy are important. Maintenance therapy with rituximab showed not only a progressionfree survival benefit but also a significant survival advantage among patients who were successfully pretreated with R-CHOP,” wrote the authors. The long-term prognosis is poor for older patients with mantle cell lymphoma. Treatment with chemotherapy achieves low rates of complete remission (CR), the authors wrote. Most older patients with mantle cell lymphoma will relapse, and better therapy is needed for this group of patients. When the trial was first initiated, the authors hoped that the fludarabinecontaining regimen would perform better than it did in this trial. However, results showed that R-FC was not more effective than R-CHOP, and the fludarabine-containing regimen was more toxic. The study enrolled 560 patients aged 60 years or older with stage II to IV mantle cell lymphoma who were randomized to receive either 6 cycles of R-FC every 28 days or to 8 cycles of R-CHOP every 21 days. Responders (n=316) were randomized to maintenance therapy with rituximab or interferon alfa, and treatment was continued until disease progression. Median age was 70 years, about 70% were male, and about 80% were stage IV at baseline. An intent-to-treat analysis for response was based on 532 patients. Rates of CR were similar for the regimens: 40% for R-FC and 34% for R-CHOP. However, more patients progressed on R-FC (14% vs 5% with R-CHOP). Four-year sur-

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

News Briefs

vival rates were significantly lower on R-FC: 47% versus 62%, respectively (P=.10). Also, more patients treated with R-FC died during first remission (10% vs 4%, respectively). Hematologic adverse events were reported more frequently in the R-FC group than in the RCHOP group, but the rates of infection were similar (17% for R-FC and 14% for R-CHOP). In the analysis of responders, maintenance therapy with rituximab reduced the risk of progression or death by 45%: progression or death occurred in 58% of those on maintenance with interferon-alfa versus 29% of those on maintenance rituximab (P=.01). Among responders to RCHOP, maintenance therapy with rituximab significantly improved overall survival at 4 years from 63% with interferon-alfa maintenance to 87% (P=.005). Toxic effects during the maintenance phase were more pronounced in the interferon-alfa group, with more patients having leukocytopenia, thrombocytopenia, and fatigue, whereas rituximab was associated with more infections. These observed differences led to differences in adherence, with an overall median treatment duration of 25 months with rituximab versus 7 months with interferon alfa. u —AG

results of 5 immunoassays using a proprietary algorithm to come up with a single numerical score indicating a woman’s likelihood of having ovarian cancer. Vermillion Inc, the diagnostic company that is marketing OVA1, released preliminary results of OVA500 and said that further details of the study have been submitted to a peer-review publication.

Blood Test for Ovarian Cancer

Weightlifting in Women at Risk for Breast Cancer–Related Lymphedema

he OVA1 blood test had a high chance of correctly identifying whether an ovarian mass was malignant prior to surgery, according to results of the OVA500 clinical trial. In a study of 494 patients, the test had 94% sensitivity in premenopausal women and 91% sensitivity in the early-stage ovarian cancer group, for an overall sensitivity of 96%. The OVA1 blood test had a negative predictive value of 98%. OVA500 was designed to evaluate the test in 2 subgroups: those with early-stage ovarian cancer, where about 50% of patients have a normal CA125 level, and premenopausal women, who typically have a high incidence of benign cysts and a low incidence of ovarian cancer. OVA1 is the first FDA-approved blood test for ovarian cancer; the test has a high sensitivity to determine if cancer is present in women with an ovarian mass prior to surgery. OVA1 is an in vitro diagnostic test that combines

Volume 1 • No 4

OVA1 is the first FDA-approved blood test for ovarian cancer; the test has a high sensitivity to determine if cancer is present in women with an ovarian mass prior to surgery. OVA500 follows a previous study published online in Obstetrics & Gynecology in March 2011 showing that use of OVA1 in place of the CA125 test correctly identified ovarian cancer 94% of the time versus 77% for CA125 in 516 women having surgery. The company hopes that results of OVA500 will support adoption and reimbursement for this blood test. u —AG

lthough weightlifting reduced the need for lymphedema treatment by 50% compared with standard treatment in breast cancer survivors who participated in the Physical Activity Lymphedema (PAL) trial, weightlifting is not without its own risks. A retrospective analysis of the PAL trial found that the rate of injury was higher in the weightlifting group compared with controls (Brown JC, et al. Oncologist. 2012;17:1120-1128). Among women assigned to weightlifting, about 1 in 5 met with a healthcare provider and either stopped or modified their weightlifting program due to injury. The study included 295 breast cancer survivors with or at risk for lymphedema; 147 were randomized to a weightlifting program. The intervention was continued for 1 year. Nine women in the weightlifting group re-

WWW.PERSONALIZEDMEDONC.COM

September 2012

News Briefs

ported 10 musculoskeletal injuries that impaired activities of daily living for at least 1 week (8 injuries were in women with lymphedema and 2 in women at risk for lymphedema). The cumulative incidence of musculoskeletal injuries in the weightlifting group among women with lymphedema was 10.2 per 100 breast cancer survivors and 3.4 per 100 breast cancer survivors among women at risk for lymphedema.

The PAL weightlifting intervention was delivered after the health fitness professionals who were going to teach weightlifting to participants underwent a 3-day training course.

The results of this analysis suggest that patients need to be informed about both the risks and benefits of exercise, and in particular, weightlifting. Clinicians and staff members who suggest weightlifting to breast cancer survivors because of its established benefits need to have the resources to promote integration of

this or any physical rehabilitation program into supportive care, wrote the authors. Since injury can occur during the first year of weightlifting, health fitness experts need to know the best way to modify exercise programs based on the needs of each patient. The exercises used in PAL were modified based on each individual’s needs. This type of intervention rests on interdisciplinary collaboration, the authors emphasized. The PAL weightlifting intervention was delivered after the health fitness professionals who were going to teach weightlifting to participants underwent a 3-day training course. Important aspects of the PAL weightlifting intervention that helped to ensure its successful delivery include preparticipation evaluations by physical therapists; patient education; ongoing surveillance by health fitness professionals for changes in symptoms that required intervention; staff resources for health fitness professionals; use of lymphedema compression garments; and periodic review of injury and other event rates through the clinical trial protocol. “Clinicians should refer breast cancer survivors to physical therapists with specific training in oncology or highly trained health fitness professionals (ie, certified cancer exercise specialists),” the authors wrote. u —AG

THIRD ANNUAL CONFERENCE

Influencing the Patient-Impact Factor

May 2-5, 2013 Westin Diplomat • Hollywood, Florida

Volume 1 • No 4

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Conference News

Severe Diarrhea Associated With Molecularly Targeted Agents Can Impact Quality of Life and Healthcare Resource Utilization Alice Goodman

preliminary report of a meta-analysis of clinical trials of molecularly targeted therapies shows that they are not benign and can add to the toxicity of standard chemotherapy. In particular, increased rates of oral mucositis and diarrhea are reported with several FDA-approved agents. Increased mucositis seen with bevacizumab and erlotinib does not appear to be clinically significant, but severe diarrhea occurs with a number of targeted agents and has a potential impact on quality of life and healthcare resource utilization. The meta-analysis provides some perspective on toxicities associated with molecularly targeted agents, and preliminary findings were presented at the 2012 Multinational Association of Supportive Care in Cancer International Symposium, held in New York City. “We know oral and gastrointestinal mucositis reduce quality of life, increase healthcare resource utilization and costs, and can lead to treatment delays and dose reductions, which interfere with treatment efficacy. There are no systematic reviews of toxicities of targeted agents, and trials are inadequately powered to look at toxicity. We get around this with meta-analysis to come up with more precise estimates of toxicities,” explained Linda Elting, DrPH, of the MD Anderson Cancer Center in Houston, Texas. Elting and colleagues searched the literature for molecularly targeted therapies, limiting the search to randomized, controlled phase 2 or 3 clinical trials of FDAapproved targeted drugs and approved indications for those drugs. The 78 studies they included compared current standard of care with standard of care plus a molecularly targeted drug. The studies had different designs, treatment regimens, and dose differences. All studies listed all-grade toxicity as well as grades 3, 4, and 5 separately. “We included only drugs for which at least 3 papers were published,” she explained.

Volume 1 • No 4

Bevacizumab was associated with an increase in allgrade oral mucositis, and the risk of grades 3 and 4 was increased 5-fold compared with standard therapy alone. The risk increases with higher doses. Elting remarked that the absolute risk of grades 3 and 4 mucositis was low, only around 3%, with the addition of bevacizumabtargeted therapy.

The 78 studies they included compared current standard of care with standard of care plus a molecularly targeted drug.

“The risk of [severe] mucositis with bevacizumab is very low and does not appear to be a clinically significant finding,” she stated. A 5-fold increase in all-grade oral mucositis was found with erlotinib, but no increase in grades 3 and 4 was observed compared with standard therapy alone. “As with bevacizumab, this is not clinically significant and is limited to low-grade oral mucositis,” she said. “Diarrhea is a hallmark of targeted therapy, so don’t be surprised by high rates,” she told listeners. With both trastuzumab and lapatinib, all grades of diarrhea are increased when added to standard therapy. A 10-fold increase in grades 3 and 4 diarrhea is reported with trastuzumab, with an absolute increased risk of 12%. “This could be important for clinical care and resource utilization,” Elting commented. “Lapatinib, erlotinib, cetuximab, gefitinib, and sorafenib are also associated with increased risk of diarrhea, including a 2- to 5-fold increase in grades 3 and 4 diarrhea, which is clinically significant and has a clear impact on quality of life and resource utilization,” she stated. u

WWW.PERSONALIZEDMEDONC.COM

September 2012

Conference News

Risk of Cardiotoxicity With Targeted Therapies Exaggerated Phoebe Starr

olecularly targeted therapies change the vascular milieu and can cause hypertension, fluid retention, and thromboembolic phenomena. However, the absolute risk of cardiotoxicity is much lower with targeted therapies compared with anthracyclines, stated Michael S. Ewer, MD, from the MD Anderson Cancer Center in Houston, Texas, at the recent meeting of the Multinational Association of Supportive Care in Cancer in New York City. The lower risk appears to be related to the different mechanisms of action of these agents; ie, cardiac damage from targeted therapy is attributable to cellular dysfunction and is reversible, while cardiac damage associated with anthracyclines is caused by cellular death and is irreversible, Ewer explained. “There has been considerable confusion and almost paranoia in some settings [related to cardiac dysfunction and targeted therapies]. Do these drugs deserve this paranoia?” he continued. “My 2 cents is that they are generally safe,” he told listeners. The risk of cardiac dysfunction with any anticancer therapy – targeted therapy or conventional chemotherapy – is increased by prior chemotherapy and prior radiation. Patients treated with molecularly targeted therapy should undergo cardiac monitoring at regular intervals but probably do not require extensive monitoring and aggressive treatment of reduction in left ventricular ejection fraction (LVEF), he continued. Patients who develop decreased LVEF and potential heart failure on targeted therapy should have targeted therapy withdrawn and receive treatment with conventional heart failure therapy; once LVEF returns to normal, targeted therapy can be restarted with the assurance of safety, Ewer told listeners. Turning to specific targeted therapies, Ewer noted that trastuzumab has a number of vascular and cardiac effects. He said that a recent Cochrane review of more than 10,000 patients showed that trastuzumab significantly in-

Volume 1 • No 4

creased the risk of congestive heart failure and LVEF decline. Yet only 2 cardiac deaths occurred in this series. “The 7-year follow-up of NSABP experience will be published soon and shows a different picture with excellent safety,” Ewer noted. Trastuzumab given in conjunction with anthracyclines is associated with increased cardiotoxicity. Explaining this phenomenon, Ewer said that anthracyclines cause oxidative damage, and ordinarily these damaged myocytes would repair, but the addition of trastuzumab to anthracyclines blocks the repair mechanisms. Therefore, timing is important when both drugs are going to be used, and they should be given separately over time, Ewer advised. The recent CLEOPATRA trial including more than 800 breast cancer patients randomized to trastuzumab plus docetaxel or docetaxel plus pertuzumab (a targeted therapy that binds to a different site on the HER2 receptor) plus trastuzumab showed no cardiac safety signal for the combination of the 2 anti-HER2 targeted therapies. “There was no major increase in cardiac toxicity,” Ewer said. Sunitinib increases the risk of hypertension in clinical trials, yet hypertension is associated with longer survival. Symptomatic and asymptomatic LVEF both increase initially on sunitinib and then plateau over time. “This shows that sunitinib does not destroy myocytes,” Ewer stated. Patients who develop hypertension on sunitinib can continue to receive it if they are treated with blood pressure–lowering medications. The incidence of cardiovascular death is low on sunitinib, Ewer noted. Bevacizumab also causes hypertension. Most of the time, bevacizumab-associated hypertension is manageable with antihypertensive therapy. If malignant hypertension develops, bevacizumab should be withdrawn. Lapatinib may cause a decrease in LVEF, but longterm use is feasible, and it may be used in combination with other drugs, Ewer said. u

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Conference News

Progress in Treating Prostate Cancer Alice Goodman

wo studies presented at the 2012 Annual Meeting of the American Society of Clinical Oncology (ASCO) suggested that abiraterone acetate (AA; Zytiga), an androgen biosynthesis inhibitor,1,2 has the potential to be used earlier in the course of prostate cancer than its current FDA indication (ie, after failure of chemotherapy in men with metastatic castrationresistant prostate cancer [CRPC]). A second interim analysis of a phase 3 trial had positive outcomes with AA in men with metastatic CRPC who had not yet received chemotherapy,1 and a preliminary phase 2 study suggested AA may have a role in the neoadjuvant setting before radical prostatectomy is performed in men with early-stage localized high-risk prostate cancer.2 In addition, results from the AFFIRM trial confirmed the superiority of enzalutamide (Xtandi, formerly MDV3100) to placebo in men with CRPC.3

nisone. The Independent Data Monitoring Committee unblinded the study early, when all primary and secondary outcomes were seen to favor AA, and patients were allowed to cross over from placebo to the AA arm. At a median follow-up of 22.3 months, median rPFS was not yet reached in the AA arm versus 8.3 months in the placebo arm (P<.0001). Median overall survival was not yet reached in the AA arm and was 27.2 months in the placebo arm (P=.0097). The interim analysis also confirmed the acceptable tolerability and safety profile of AA in this setting.

Abiraterone in Chemotherapy-Naive Metastatic CRPC1

Neoadjuvant Abiraterone Acetate2

Results of the second interim analysis of COU-AA302 showed that AA plus prednisone significantly improved radiographic progression-free survival (rPFS), with a strong trend toward increased overall survival (OS) compared with placebo plus prednisone in men with metastatic CRPC who had not received chemotherapy. This study evaluated earlier use of AA than the current FDA indication for use following failure of chemotherapy in CRPC. “This is the first randomized trial to demonstrate both an overall survival and progression-free survival benefit in chemotherapy-naive patients with metastatic CRPC and show that inhibition of persistent extragonadal androgen synthesis significantly delays initiation of cytotoxic chemotherapy,” stated lead author Charles J. Ryan, MD, of the University of California San Francisco. The study enrolled 1088 patients at 151 centers in 12 countries. Patients were randomized 1:1 to AA (1 g) plus prednisone (5 mg BID) versus placebo plus pred-

Volume 1 • No 4

Secondary results of the AFFIRM trial confirmed the superiority of enzalutamide to placebo in men with CRPC.

Another study of even earlier use of AA suggests that the drug will find a role prior to the development of metastatic prostate cancer. Preadjuvant treatment with 6 months of AA given concurrently with leuprolide acetate, a hormonal therapy, and prednisone prior to radical prostatectomy successfully eradicated prostate cancer cells in about 30% of men with high-risk early prostate cancer in a randomized phase 2 trial. “These results are particularly amazing in this incredibly high-risk group of patients, and suggest that this combination therapy could improve outcomes for a substantial number of men with early high-risk prostate cancer,” stated lead author Mary-Ellen Taplin, MD, of Harvard Medical School and the Dana-Farber Cancer Institute in Boston, Massachusetts. This is a preliminary study, and larger, longer trials will be needed to establish a role for AA plus hormone therapy in the neoadjuvant setting. The phase 2 trial included 58 men who were defined as high risk because they had at least 1 of the following

WWW.PERSONALIZEDMEDONC.COM

September 2012

Conference News

features: ≥3 positive biopsies; Gleason score ≥7 (71% of men had scores of 8-10); prostate-specific antigen (PSA) >20 ng/mL (19%); T3, T4 bulky disease (24%); or PSA velocity >2 ng/mL/year (16%). Men with extranodal disease were allowed to enroll. The men were randomized to receive 3 months of treatment with leuprolide acetate alone or 3 months of leuprolide acetate plus AA plus low-dose prednisone. Prednisone 5 mg/day was given with AA to prevent side effects associated with this drug. After 3 months, a prostate biopsy was performed to measure serum testosterone and dihydrotestosterone levels, after which the men received 12 more weeks of leuprolide acetate/ AA/prednisone. At 3 months, 10% of the men who were treated with leuprolide acetate/AA/prednisone had pathologic complete response (pCR), compared with 4% of those treated with leuprolide acetate alone; near pCR was observed in 24% and 11%, respectively.

PSA response to enzalutamide was high; 54% of patients in the enzalutamide group had >50% declines in PSA level.

Enzalutamide in Metastatic CRPC3 Enzalutamide, an androgen receptor signaling inhibitor, was superior to placebo for both the primary and secondary end points in the phase 3 AFFIRM trial in men with progressive CRPC. Primary end point results for OS reported earlier showed that enzalutamide significantly improved OS by about 4.8 months compared with the placebo group; the risk of death was reduced by 37% in men randomized to enzalutamide (P<.0001).4,5 “These are the best survival rates we have seen in the post-chemotherapy setting,” said Johann S. De Bono, MD, ChB, of the Institute for Cancer Research and the Royal Marsden NHS Foundation Trust, United Kingdom. At the ASCO Annual Meeting, De Bono presented new data on secondary outcomes in AFFIRM. Enzalutamide was superior to placebo for the following meas-

Volume 1 • No 4

ures: PSA response, soft tissue objective response, and quality-of-life response as assessed by FACT-P; as well as such indicators of disease progression as rPFS and time to first skeletal-related event. AFFIRM randomized 800 patients to enzalutamide and 399 to placebo. Median age was 69 years. At baseline, both groups were well matched for demographic and disease characteristics. Almost 50% of the group assigned to enzalutamide had received prior hormone therapy compared with 53% of placebo patients; median number of prior chemotherapy regimens was similar between groups. PSA response to enzalutamide was high; 54% of patients in the enzalutamide group had >50% declines in PSA level. Following a prespecified interim analysis, the Independent Data Monitoring Committee recommended that the AFFIRM trial be halted and unblinded, and eligible patients in the placebo arm were allowed to cross over to enzalutamide. Enzalutamide was well tolerated. A greater percentage of patients in the treated group reported fatigue, and 5 patients had seizures versus none with placebo. On August 31, 2012, enzalutamide (Xtandi; Medivation) was approved by the FDA for the treatment of patients with metastatic CRPC who have previously received docetaxel. u

References 1. Ryan CJ, Smith MR, De Bono JS, et al; on behalf of the COU-AA-302 Investigators. Interim analysis (IA) results of COU-AA-302, a randomized, phase III study of abiraterone acetate (AA) in chemotherapy-naive patients (pts) with metastatic castration-resistant prostate cancer (mCRPC). J Clin Oncol. 2012;30(suppl). Abstract LBA4518. 2. Taplin M-E, Montgomery RB, Logothetis C, et al. Effect of neoadjuvant abiraterone acetate (AA) plus leuprolide acetate (LHRHa) on PSA, pathological complete response (pCR), and near pCR in localized high-risk prostate cancer (LHRPC): results of a randomized phase II study. J Clin Oncol. 2012;30(suppl). Abstract 4521. 3. De Bono JS, Fizazi K, Saad F, et al; for the AFFIRM Investigators. Primary, secondary, and quality-of-life endpoint results from the phase III AFFIRM study of MDV3100, an androgen receptor signaling inhibitor. J Clin Oncol. 2012;30(suppl). Abstract 4519. 4. Scher HI, Fizazi K, Saad F, et al; for the AFFIRM Investigators. Effect of MDV3100, an androgen receptor signaling inhibitor (ARSI), on overall survival in patients with prostate cancer postdocetaxel: results from the phase III AFFIRM study. J Clin Oncol. 2012;30(suppl 5). Abstract LBA1. 5. Scher HI, Fizazi K, Saad F, et al; the AFFIRM Investigators. Increased survival with enzalutamide in prostate cancer after chemotherapy [published online ahead of print August 15, 2012]. N Engl J Med.

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Conference News

Mucositis Management to Become More Personalized Caroline Helwick

new appreciation of the pathobiological foundation of mucositis, and the application of genomics to risk assessment, heralds an individualized and more effective approach to intervention for this costly and often disabling toxicity, according to specialists who spoke at a session on mucosal injury during the 2012 Annual Meeting of the American Society of Clinical Oncology.

New Mechanistic Understanding Old concepts are being replaced by a pathobiological paradigm that better captures the underlying mechanism and allows for more effective interventions. Mucositis is now “about bioinformatics, targeted treatment, risk prediction, and other exciting frontiers,” said Douglas Peterson, DMD, PhD, of the University of Connecticut Health Center in Farmington. Stephen T. Sonis, DMD, DMSc, of Biomodels in Watertown, Massachusetts, described the biological cascade leading to mucosal injury as one involving the mesenchyme, extracellular matrix, and epithelium; the local environment; and the microflora. Once thought of as a direct epithelial process in which chemotherapy or radiotherapy killed cells, the development of mucositis is actually a multifactorial process within the diverse tissues of the submucosa, he said. “The cascade of events starts with oxidative stress, followed by an innate immune response, leading to a primary damage response, initiation of signaling pathways, amplification and feedback, then ulceration, surface colonization, and healing,” he said. The involvement of so many processes means, he said, “that in developing drug targets and in looking for risk predictors, we have a bigger palate to go after, versus just focusing on epithelial cells, as in the historical paradigm.” Emerging areas of research are the local environment of the gastrointestinal tract and mouth, especially salivary

Volume 1 • No 4

and intestinal proteins secreted in response to mucosal injury, as well as changes in bacterial flora, Sonis said.

Targeted Agents May Not Be Much Better Dorothy Keefe, MD, MBBS, of Royal Adelaide Hospital in Australia, cautioned against thinking that new targeted agents will carry less risk of mucositis. The mTOR inhibitors, for example, produce a unique mucositis pattern.

Old concepts are being replaced by a pathobiological paradigm that better captures the underlying mechanism and allows for more effective interventions. “Every new drug class brings new toxicities, despite the temptation to think that ‘targeted’ equals ‘nontoxic,’ ” she said. The toxicities of targeted therapies are often clinically significant, long-lasting, and not reversible, she added. She pointed out that signaling pathways may be related to both the toxicity and oncogenesis, and interfering with pathways is “tricky territory.” Understanding of mechanisms, she said, is key to optimal management. “Time-tested empiric foundational approaches” that have been used for decades will continue to be important in the new frontier of targeted cancer therapies and their toxicities, Peterson said. These include patient education and compliance, simple wound care approaches, structured approaches to pain control, adequate hydration and nutritional support, surveillance, and treatment of infectious complications. “The problem is that these approaches are not fundamentally targeting the pathobiology,” he said. “The

WWW.PERSONALIZEDMEDONC.COM

September 2012

Conference News

Novel Mouth Rinse Reduces Course and Severity of Oral Mucositis

opical administration of a novel mouth rinse, AG013, appears safe, well tolerated, and effective in reducing the severity and course of oral mucositis (OM) in patients receiving induction chemotherapy in a study presented at the 2012 ASCO Annual Meeting. (Abstract 9024). AG013 is a mouth rinse composed of a recombinant Lactococcus lactis engineered to secrete human trefoil factor 1 (hTFF1) and deficient in the gene encoding thymidylate synthase. TFFs have wound-healing properties and are protective of mucosal tissues. The compound was evaluated in 25 patients who developed symptomatic oral mucositis after induction chemotherapy for head and neck cancer in a phase 1B, multicenter, single-blind, placebo-controlled study reported by Sewanti Atul Limaye, MD, of the Dana-Farber Cancer Institute in Boston, Massachusetts. Three dosing cohorts were evaluated and compared with placebo recipients. Patients receiving AG013 on any dosing schedule had a lower percentage of days with OM and fewer unplanned office and emergency room visits compared with patients who received placebo. Responses (≤1 day of ulcerative OM) were observed in 29% of AG013 patients but in none of the placebo patients. Ulcerative OM was observed during 35% to 40% of study days for patients receiving the mouth rinse, compared with 60% of study days in the placebo group. The absolute reduction in the percentage of days with ulcerative OM, with the use of the novel mouth rinse, was 35%. No differences were noted in mouth and throat soreness, opioid use, or gastrostomy tube placement. u

Volume 1 • No 4

new world order, where we are headed, will include individualized risk profiles and customized therapies.”

Risk Prediction “Personalized cancer medicine involves both tumor and toxicity. It is not good enough to personalize the cancer treatment. We have to personalize the supportive care as well, and risk prediction for toxicity is becoming a reality,” Keefe said. “We are at a very serendipitous time,” Sonis agreed. “Risk prediction has become possible through the evolution of genomics.” Single-nucleotide polymorphisms (SNPs) are the most common form of variation in the genome. SNPs can reside intracellularly (and affect transcription) or extracellularly (and be an indicator of toxicity risk). Advances in bioinformatics are making it possible to select clusters of SNPs, out of millions, that can predict for toxicity. This is already possible for patients undergoing conditioning regimens for autologous stem cell transplant, 40% of whom will develop severe mucositis and 60% of whom will therefore be treated unnecessarily, he said. In a retrospective analysis of myeloma and lymphoma patients undergoing transplant at a single center, Sonis and his team identified 51 patients who developed oral mucositis and 102 who did not. They looked for SNPs in the DNA of patients’ saliva and found a cluster of 82 SNPs that predicted for mucositis with 99.3% accuracy. The area under the ROC (receiver operating characteristic) curve was 0.997 (0.9-1.0 is considered an excellent predictor). The ROC for mammography is 0.74, he noted for comparison. A multicenter study of the model is planned, and this model is being further developed for commercialization. “We were thrilled,” Sonis commented. “This approach should be a game changer in terms of our ability to predict mucositis and other biologically based toxicities. This means we can be much more precise in developing risk assessments, understanding the patient’s response to risk, and being able to favorably impact toxicity with targeted interventions for the patient at risk.” u

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Conference News

Targeted Drug Leads to Marked Responses in NSCLC Don Schrader

drug that targets a previously overlooked mutation led to objective responses in 8 of 14 patients with advanced non–small cell lung cancer (NSCLC), according to results of a proof-ofprinciple study. Some patients had symptomatic relief within days of beginning treatment with crizotinib, Alice T. Shaw, MD, PhD, reported at the Annual Meeting of the American Society of Clinical Oncology. The drug targets a ROS1 mutation that occurs in 1% to 2% of NSCLC tumors. Overall, the drug was well tolerated, as the most common adverse event was a mild visual disturbance that affected almost all of the patients. “ROS1 rearrangement defines a distinct subset of non–small cell lung cancer,” said Shaw, an attending physician in thoracic oncology at Massachusetts General Hospital in Boston. “Crizotinib demonstrates marked antitumor activity in patients with advanced ROS1-positive non–small cell lung cancer. These results validate ROS1 as a therapeutic target in lung cancer.” Some patients had substantial resolution of tumors within weeks of starting treatment, she added. Identified about 20 years ago, ROS1 has a poorly defined normal function and only recently was found to play a role in a subset of NSCLC tumors. ROS1 activates signaling pathways common to several receptor tyrosine kinases, said Shaw. Of 15 patients treated to date, 12 remained on ther-

apy, and 14 could be evaluated for response. In addition to the 8 patients who had objective responses, 4 others had stable disease for 8 weeks or longer, resulting in a disease control rate of 79%. Median treatment duration was 25.7 weeks.

Identified about 20 years ago, ROS1 has a poorly defined normal function and only recently was found to play a role in a subset of NSCLC tumors. Aside from visual impairment, adverse events included transient liver enzyme elevation, diarrhea, hypophosphatemia, peripheral edema, dysgeusia, nausea, vomiting, elevated alkaline phosphatase, neutropenia, and sinus bradycardia. Invited discussant Gregory Riely, MD, PhD, said the results add to the ongoing transformation of NSCLC from a single entity into a heterogeneous disease associated with multiple genetic mutations and profiles. “We can’t solely identify these patients by smoking history, ethnicity, age. We really need to test all patients,” said Riely, a thoracic oncologist at Memorial Sloan-Kettering Cancer Center in New York. Despite the limited clinical experience, the marked responses that occurred in some of the patients have convinced Riely to start giving crizotinib to all patients with confirmed ROS1-positive NSCLC. u

INTERVIEW WITH THE INNOVATORS An exclusive PMO series Personalized Medicine in Oncology™ is pleased to offer insightful interviews with leaders in oncology about their approach to personalized medicine. To watch our interviews, visit www.PersonalizedMedOnc.com/videolibrary

Volume 1 • No 4

WWW.PERSONALIZEDMEDONC.COM

September 2012

Conference News

Progressive Myeloma Responds to Monoclonal Antibody Don Schrader

ore than 80% of patients with relapsed or refractory multiple myeloma responded to a monoclonal antibody against a cell surface protein expressed by almost all myeloma cells, results of a phase 2 clinical trial showed. All patients received lenalidomide and dexamethasone and were randomized to 10 or 20 mg of elotuzumab.

Elotuzumab is a humanized monoclonal antibody that targets the CS1 glycoprotein expressed by more than 95% of myeloma cells. Normal cells express little or no CS1.

The overall response rate included 92% of patients treated with 10 mg of elotuzumab and 73% of those who received 20 mg. After a median follow-up of 17.2 months, the median progression-free survival (PFS) had not been reached among patients in the 10-mg cohort, whereas patients assigned to 20 mg of elotuzumab had a median PFS of 18 months. “These data are really encouraging when compared to those achieved with lenalidomide and high-dose dexamethasone,” Philippe Moreau, MD, a hematologic oncologist at Hotel-Dieu University Hospital in Nantes,

France, said at the Annual Meeting of the American Society of Clinical Oncology. An analysis limited to patients who had received only 1 prior regimen showed that all patients treated with the 10-mg dose of elotuzumab had objective responses, as did 82% of those who received the higher dose of the monoclonal antibody. “[These results] indicate that this combination could also be effective in frontline treatment,” Moreau added. Elotuzumab is a humanized monoclonal antibody that targets the CS1 glycoprotein expressed by more than 95% of myeloma cells. Normal cells express little or no CS1. Moreau presented results of a trial involving 73 patients with previously treated multiple myeloma. A majority of the patients had received 2 or more prior regimens, and more than 60% of the patients had received lenalidomide and bortezomib. The results showed that 33 of 36 patients in the 10mg group had objective responses, including 5 complete responses. In the 20-mg arm, 30 of 37 patients responded to elotuzumab. Moreau reported that 48% of the entire study population had responses that met criteria for very good partial responses. The most common grade 3/4 adverse events were neutropenia, lymphopenia, and thrombocytopenia, each of which occurred in 16% of patients. u

SECOND ANNUAL CONFERENCE #

Clinical Approaches to Targeted Technologies# October 4-6, 2013

The Seaport Boston Hotel • 1 Seaport Lane • Boston, MA 02210

✓REGISTER TODAY AT www.globalbiomarkersconsortium.com 24

Volume 1 • No 4

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

The Next Generation in Oncologic Care

PM O

The official publication of

Global biomarkers Consortium Clinical Approaches

PERSONALIZED MEDICINE IN ONCOLOGY

to Targeted Technologies

Implementing the Promise of Prognostic Precision into Personalized Cancer Care TM

Join us on our journey to realize the tremendous possibilities of improving cancer prevention, diagnosis, and treatment through a new medical model of personalized care. Where are

Volume 1 â&#x20AC;˘ No 1

you on the path?

WWW.PERSONALIZEDMEDONC.COM www.PersonalizedMedOnc.com

May 2012

PMOHouseAd1

TREANDA速 (bendamustine HCI) for Injection is his chemo.

This is his therapy.

Single-agent TREANDA tripled median PFS* TREANDA is indicated for the treatment of patients with chronic lymphocytic leukemia (CLL). Efficacy relative to first-line therapies other than chlorambucil has not been established. PROGRESSION-FREE SURVIVAL (PFS): CHRONIC LYMPHOCYTIC LEUKEMIA (CLL) Survival distribution function

TREANDA (n=153)

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1

Chlorambucil (n=148)

18 months median PFS

6 months median PFS

P<.0001 HRâ&#x20AC; =0.27 (95% CIâ&#x20AC;¡: 0.17, 0.43)

Months *TREANDA (95% CI: 11.7, 23.5) vs chlorambucil (95% CI: 5.6, 8.6). â&#x20AC; HR=hazard ratio. â&#x20AC;¡ CI=confidence interval.

t 53&"/%" XBT DPNQBSFE XJUI DIMPSBNCVDJM JO B SBOEPNJ[FE PQFO MBCFM QIBTF USJBM JO USFBUNFOU OBÃ&#x2022;WF QBUJFOUT XJUI #JOFU TUBHF # PS $ 3BJ TUBHFT * *7 $-- XIP SFRVJSFE USFBUNFOU / t 53&"/%" JT BENJOJTUFSFE XJUI B DPOWFOJFOU EPTJOH TDIFEVMF o 5IF SFDPNNFOEFE EPTF GPS 53&"/%" JT NH N2 BENJOJTUFSFE JOUSBWFOPVTMZ PWFS NJOVUFT PO %BZT BOE PG B EBZ USFBUNFOU DZDMF VQ UP DZDMFT o *O UIF QIBTF USJBM QBUJFOUT SFDFJWFE DIMPSBNCVDJM BU B EPTF PG NH LH PSBMMZ PO %BZT BOE O PG B EBZ USFBUNFOU DZDMF VQ UP DZDMFT t *O UIF QJWPUBM QIBTF USJBM UIF NPTU DPNNPO OPO IFNBUPMPHJD BEWFSTF SFBDUJPOT GSFRVFODZ â&#x2030;¥ XFSF QZSFYJB OBVTFB BOE WPNJUJOH O 5IF NPTU DPNNPO IFNBUPMPHJD BCOPSNBMJUJFT GSFRVFODZ â&#x2030;¥ XFSF BOFNJB UISPNCPDZUPQFOJB OFVUSPQFOJB MZNQIPQFOJB BOE MFVLPQFOJB O

Important Safety Information t 4FSJPVT BEWFSTF SFBDUJPOT JODMVEJOH NZFMPTVQQSFTTJPO JOGFDUJPOT JOGVTJPO SFBDUJPOT BOE BOBQIZMBYJT UVNPS MZTJT TZOESPNF TLJO SFBDUJPOT JODMVEJOH 4+4 5&/ PUIFS NBMJHOBODJFT BOE FYUSBWBTBUJPO IBWF CFFO BTTPDJBUFE XJUI 53&"/%" 4PNF SFBDUJPOT TVDI BT NZFMPTVQQSFTTJPO JOGFDUJPOT BOE 4+4 5&/ XIFO 53&"/%" XBT BENJOJTUFSFE DPODPNJUBOUMZ XJUI BMMPQVSJOPM BOE PUIFS NFEJDBUJPOT LOPXO UP DBVTF 4+4 5&/ IBWF CFFO GBUBM 1BUJFOUT should be monitored closely for these reactions and treated promptly if any occur t "EWFSTF SFBDUJPOT NBZ SFRVJSF JOUFSWFOUJPOT TVDI BT EFDSFBTJOH UIF EPTF PG 53&"/%" PS XJUIIPMEJOH PS EFMBZJOH USFBUNFOU t 53&"/%" JT DPOUSBJOEJDBUFE JO QBUJFOUT XJUI B LOPXO IZQFSTFOTJUJWJUZ UP CFOEBNVTUJOF PS NBOOJUPM 8PNFO TIPVME CF BEWJTFE UP BWPJE CFDPNJOH QSFHOBOU XIJMF VTJOH 53&"/%" t 5IF NPTU DPNNPO OPO IFNBUPMPHJD BEWFSTF SFBDUJPOT GPS $-- GSFRVFODZ Ã¶ BSF QZSFYJB OBVTFB BOE WPNJUJOH 5IF NPTU DPNNPO IFNBUPMPHJD BCOPSNBMJUJFT GSFRVFODZ Ã¶ BSF BOFNJB UISPNCPDZUPQFOJB OFVUSPQFOJB MZNQIPQFOJB BOE MFVLPQFOJB

Discover the elements of efficacy and safety LEARN MORE AT WWW.TREANDA.COM Please see accompanying brief summary of full Prescribing Information.

The Grade 3 and 4 hematology laboratory test values by treatment group in the randomized CLL clinical study are described in Table 2. These findings confirm the myelosuppressive effects seen in patients treated with TREANDA. Red blood cell transfusions were administered to 20% of patients receiving TREANDA compared with 6% of patients receiving chlorambucil. Brief Summary of Prescribing Information for Chronic Lymphocytic Leukemia INDICATIONS AND USAGE: TREANDA is indicated for the treatment of patients with chronic lymphocytic leukemia (CLL). Efficacy relative to first line therapies other than chlorambucil has not been established. CONTRAINDICATIONS: TREANDA is contraindicated in patients with a known hypersensitivity (eg, anaphylactic and anaphylactoid reactions) to bendamustine or mannitol. [See Warnings and Precautions] WARNINGS AND PRECAUTIONS: Myelosuppression. Patients treated with TREANDA are likely to experience myelosuppression. In the two NHL studies, 98% of patients had Grade 3-4 myelosuppression. Three patients (2%) died from myelosuppression-related adverse reactions; one each from neutropenic sepsis, diffuse alveolar hemorrhage with Grade 3 thrombocytopenia, and pneumonia from an opportunistic infection (CMV). In the event of treatment-related myelosuppression, monitor leukocytes, platelets, hemoglobin (Hgb), and neutrophils closely. In the clinical trials, blood counts were monitored every week initially. Hematologic nadirs were observed predominantly in the third week of therapy. Hematologic nadirs may require dose delays if recovery to the recommended values have not occurred by the first day of the next scheduled cycle. Prior to the initiation of the next cycle of therapy, the ANC should be â&#x2030;Ľ 1 x 109/L and the platelet count should be â&#x2030;Ľ 75 x 109/L. [See Dosage and Administration]. Infections. Infection, including pneumonia and sepsis, has been reported in patients in clinical trials and in post-marketing reports. Infection has been associated with hospitalization, septic shock and death. Patients with myelosuppression following treatment with TREANDA are more susceptible to infections. Patients with myelosuppression following TREANDA treatment should be advised to contact a physician if they have symptoms or signs of infection. Infusion Reactions and Anaphylaxis. Infusion reactions to TREANDA have occurred commonly in clinical trials. Symptoms include fever, chills, pruritus and rash. In rare instances severe anaphylactic and anaphylactoid reactions have occurred, particularly in the second and subsequent cycles of therapy. Monitor clinically and discontinue drug for severe reactions. Patients should be asked about symptoms suggestive of infusion reactions after their first cycle of therapy. Patients who experienced Grade 3 or worse allergic-type reactions were not typically rechallenged. Measures to prevent severe reactions, including antihistamines, antipyretics and corticosteroids should be considered in subsequent cycles in patients who have previously experienced Grade 1 or 2 infusion reactions. Discontinuation should be considered in patients with Grade 3 or 4 infusion reactions. Tumor Lysis Syndrome. Tumor lysis syndrome associated with TREANDA treatment has been reported in patients in clinical trials and in post-marketing reports. The onset tends to be within the first treatment cycle of TREANDA and, without intervention, may lead to acute renal failure and death. Preventive measures include maintaining adequate volume status, and close monitoring of blood chemistry, particularly potassium and uric acid levels. Allopurinol has also been used during the beginning of TREANDA therapy. However, there may be an increased risk of severe skin toxicity when TREANDA and allopurinol are administered concomitantly. Skin Reactions. A number of skin reactions have been reported in clinical trials and post-marketing safety reports. These events have included rash, toxic skin reactions and bullous exanthema. Some events occurred when TREANDA was given in combination with other anticancer agents, so the precise relationship to TREANDA is uncertain. In a study of TREANDA (90 mg/m2) in combination with rituximab, one case of toxic epidermal necrolysis (TEN) occurred. TEN has been reported for rituximab (see rituximab package insert). Cases of Stevens-Johnson syndrome (SJS) and TEN, some fatal, have been reported when TREANDA was administered concomitantly with allopurinol and other medications known to cause these syndromes. The relationship to TREANDA cannot be determined. Where skin reactions occur, they may be progressive and increase in severity with further treatment. Therefore, patients with skin reactions should be monitored closely. If skin reactions are severe or progressive, TREANDA should be withheld or discontinued. Other Malignancies. There are reports of pre-malignant and malignant diseases that have developed in patients who have been treated with TREANDA, including myelodysplastic syndrome, myeloproliferative disorders, acute myeloid leukemia and bronchial carcinoma. The association with TREANDA therapy has not been determined. Extravasation. There are postmarketing reports of bendamustine extravasations resulting in hospitalizations from erythema, marked swelling, and pain. Precautions should be taken to avoid extravasations, including monitoring of the intravenous infusion site for redness, swelling, pain, infection, and necrosis during and after administration of TREANDA. Use in Pregnancy. TREANDA can cause fetal harm when administered to a pregnant woman. Single intraperitoneal doses of bendamustine in mice and rats administered during organogenesis caused an increase in resorptions, skeletal and visceral malformations, and decreased fetal body weights. ADVERSE REACTIONS: The data described below reflect exposure to TREANDA in 153 patients who participated in an actively-controlled trial for the treatment of CLL. 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. The following serious adverse reactions have been associated with TREANDA in clinical trials and are discussed in greater detail in other sections [See Warnings and Precautions] of the label: Myelosuppression; Infections; Infusion Reactions and Anaphylaxis; Tumor Lysis Syndrome; Skin Reactions; Other Malignancies. Clinical Trials Experience in CLL. The data described below reflect exposure to TREANDA in 153 patients. TREANDA was studied in an active-controlled trial. The population was 45-77 years of age, 63% male, 100% white, and had treatment naĂŻve CLL. All patients started the study at a dose of 100 mg/m2 intravenously over 30 minutes on days 1 and 2 every 28 days. Adverse reactions were reported according to NCI CTC v.2.0. In the randomized CLL clinical study, non-hematologic adverse reactions (any grade) in the TREANDA group that occurred with a frequency greater than 15% were pyrexia (24%), nausea (20%), and vomiting (16%). Other adverse reactions seen frequently in one or more studies included asthenia, fatigue, malaise, and weakness; dry mouth; somnolence; cough; constipation; headache; mucosal inflammation; and stomatitis. Worsening hypertension was reported in 4 patients treated with TREANDA in the randomized CLL clinical study and none treated with chlorambucil. Three of these 4 adverse reactions were described as a hypertensive crisis and were managed with oral medications and resolved. The most frequent adverse reactions leading to study withdrawal for patients receiving TREANDA were hypersensitivity (2%) and pyrexia (1%). Table 1 contains the treatment emergent adverse reactions, regardless of attribution, that were reported in â&#x2030;Ľ 5% of patients in either treatment group in the randomized CLL clinical study. Table 1: Non-Hematologic Adverse Reactions Occurring in Randomized CLL Clinical Study in at Least 5% of Patients Number (%) of patients TREANDA Chlorambucil (N=153) (N=143) System organ class Preferred term All Grades Grade 3/4 All Grades Grade 3/4 Total number of patients with at least 1 adverse reaction 121 (79) 52 (34) 96 (67) 25 (17) Gastrointestinal disorders Nausea 31 (20) 1 (<1) 21 (15) 1 (<1) Vomiting 24 (16) 1 (<1) 9 (6) 0 Diarrhea 14 (9) 2 (1) 5 (3) General disorders and administration site conditions Pyrexia 36 (24) 6 (4) 8 (6) 2 (1) Fatigue 14 (9) 2 (1) 8 (6) 0 Asthenia 13 (8) 0 6 (4) 0 Chills 9 (6) 0 1 (<1) 0 Immune system disorders Hypersensitivity 7 (5) 2 (1) 3 (2) 0 Infections and infestations Nasopharyngitis 10 (7) 0 12 (8) 0 Infection 9 (6) 3 (2) 1 (<1) 1 (<1) Herpes simplex 5 (3) 0 7 (5) 0 Investigations Weight decreased 11 (7) 0 5 (3) 0 Metabolism and nutrition disorders Hyperuricemia 11 (7) 3 (2) 2 (1) 0 Respiratory, thoracic and mediastinal disorders Cough 6 (4) 1 (<1) 7 (5) 1 (<1) Skin and subcutaneous tissue disorders Rash 12 (8) 4 (3) 7 (5) 3 (2) Pruritus 8 (5) 0 2 (1) 0

Table 2: Incidence of Hematology Laboratory Abnormalities in Patients Who Received TREANDA or Chlorambucil in the Randomized CLL Clinical Study Chlorambucil TREANDA (N=141) (N=150) All Grades Grade 3/4 All Grades Grade 3/4 Laboratory Abnormality n (%) n (%) n (%) n (%) Hemoglobin Decreased 134 (89) 20 (13) 115 (82) 12 (9) Platelets Decreased 116 (77) 16 (11) 110 (78) 14 (10) Leukocytes Decreased 92 (61) 42 (28) 26 (18) 4 (3) Lymphocytes Decreased 102 (68) 70 (47) 27 (19) 6 (4) Neutrophils Decreased 113 (75) 65 (43) 86 (61) 30 (21) In the randomized CLL clinical study, 34% of patients had bilirubin elevations, some without associated significant elevations in AST and ALT. Grade 3 or 4 increased bilirubin occurred in 3% of patients. Increases in AST and ALT of Grade 3 or 4 were limited to 1% and 3% of patients, respectively. Patients treated with TREANDA may also have changes in their creatinine levels. If abnormalities are detected, monitoring of these parameters should be continued to ensure that significant deterioration does not occur. Post-Marketing Experience. The following adverse reactions have been identified during post-approval use of TREANDA. Because these reactions are reported voluntarily from a population of uncertain size, it is not always possible to reliably estimate their frequency or establish a causal relationship to drug exposure: anaphylaxis; and injection or infusion site reactions including phlebitis, pruritus, irritation, pain, and swelling. Skin reactions including SJS and TEN have occurred when TREANDA was administered concomitantly with allopurinol and other medications known to cause these syndromes. [See Warnings and Precautions] OVERDOSAGE: The intravenous LD of bendamustine HCl is 240 mg/m2 in the mouse and rat. Toxicities included sedation, tremor, ataxia, convulsions and respiratory distress. Across all clinical experience, the reported maximum single dose received was 280 mg/m2. Three of four patients treated at this dose showed ECG changes considered dose-limiting at 7 and 21 days post-dosing. These changes included QT prolongation (one patient), sinus tachycardia (one patient), ST and T wave deviations (two patients), and left anterior fascicular block (one patient). Cardiac enzymes and ejection fractions remained normal in all patients. No specific antidote for TREANDA overdose is known. Management of overdosage should include general supportive measures, including monitoring of hematologic parameters and ECGs. DOSAGE AND ADMINISTRATION: Dosing Instructions for CLL. Recommended Dosage: The recommended dose is 100 mg/m2 administered intravenously over 30 minutes on Days 1 and 2 of a 28-day cycle, up to 6 cycles. Dose Delays, Dose Modifications and Reinitiation of Therapy for CLL: TREANDA administration should be delayed in the event of Grade 4 hematologic toxicity or clinically significant â&#x2030;ĽÂ Grade 2 non-hematologic toxicity. Once non-hematologic toxicity has recovered to â&#x2030;¤Â Grade 1 and/or the blood counts have improved [Absolute Neutrophil Count (ANC) â&#x2030;ĽÂ 1 x 109/L, platelets â&#x2030;ĽÂ 75 x 109/L], TREANDA can be reinitiated at the discretion of the treating physician. In addition, dose reduction may be warranted. [See Warnings and Precautions] Dose modifications for hematologic toxicity: for Grade 3 or greater toxicity, reduce the dose to 50 mg/m2 on Days 1 and 2 of each cycle; if Grade 3 or greater toxicity recurs, reduce the dose to 25 mg/m2 on Days 1 and 2 of each cycle. Dose modifications for non-hematologic toxicity: for clinically significant Grade 3 or greater toxicity, reduce the dose to 50 mg/m2 on Days 1 and 2 of each cycle. Dose re-escalation in subsequent cycles may be considered at the discretion of the treating physician. Reconstitution/Preparation for Intravenous Administration. t Aseptically SFDPOTUJUVUF FBDI 53&"/%" WJBM BT GPMMPXT t NH 53&"/%" WJBM "EE N- PG POMZ Sterile Water for Injection, USP t NH 53&"/%" WJBM "EE N- PG POMZ Sterile Water for Injection, USP. Shake well to yield a clear, colorless to a pale yellow solution with a bendamustine HCl concentration of 5 mg/mL. The lyophilized powder should completely dissolve in 5 minutes. If particulate matter is observed, the reconstituted product should not be VTFE t "TFQUJDBMMZ XJUIESBX UIF WPMVNF OFFEFE GPS UIF SFRVJSFE EPTF CBTFE PO NH N- DPODFOUSBUJPO BOE immediately transfer to a 500 mL infusion bag of 0.9% Sodium Chloride Injection, USP (normal saline). As an alternative to 0.9% Sodium Chloride Injection, USP (normal saline), a 500 mL infusion bag of 2.5% Dextrose/0.45% Sodium Chloride Injection, USP, may be considered. The resulting final concentration of bendamustine HCl in the infusion bag should be within 0.2â&#x20AC;&#x201C;0.6 mg/mL. The reconstituted solution must be transferred to the infusion bag within 30 minutes of reconstitution. After transferring, thoroughly mix the contents of the infusion bag. The BENJYUVSF TIPVME CF B DMFBS BOE DPMPSMFTT UP TMJHIUMZ ZFMMPX TPMVUJPO t 6TF 4UFSJMF 8BUFS GPS *OKFDUJPO 641 GPS reconstitution and then either 0.9% Sodium Chloride Injection, USP, or 2.5% Dextrose/0.45% Sodium Chloride *OKFDUJPO 641 GPS EJMVUJPO BT PVUMJOFE BCPWF /P PUIFS EJMVFOUT IBWF CFFO TIPXO UP CF DPNQBUJCMF t 1BSFOUFSBM drug products should be inspected visually for particulate matter and discoloration prior to administration whenever solution and container permit. Any unused solution should be discarded according to institutional procedures for antineoplastics. Admixture Stability. TREANDA contains no antimicrobial preservative. The admixture should be prepared as close as possible to the time of patient administration. Once diluted with either 0.9% Sodium Chloride Injection, USP, or 2.5% Dextrose/0.45% Sodium Chloride Injection, USP, the final admixture is stable for 24 hours when stored refrigerated (2-8Â°C or 36-47Â°F) or for 3 hours when stored at room temperature (15-30Â°C or 59-86Â°F) and room light. Administration of TREANDA must be completed within this period. DOSAGE FORMS AND STRENGTHS: TREANDA for Injection single-use vial containing either 25 mg or 100 mg of bendamustine HCl as white to off-white lyophilized powder. HOW SUPPLIED/STORAGE AND HANDLING: Safe Handling and Disposal. As with other potentially toxic anticancer agents, care should be exercised in the handling and preparation of solutions prepared from TREANDA. The use of gloves and safety glasses is recommended to avoid exposure in case of breakage of the vial or other accidental spillage. If a solution of TREANDA contacts the skin, wash the skin immediately and thoroughly with soap and water. If TREANDA contacts the mucous membranes, flush thoroughly with water. Procedures for the proper handling and disposal of anticancer drugs should be considered. Several guidelines on the subject have been published. There is no general agreement that all of the procedures recommended in the guidelines are necessary or appropriate. How Supplied. TREANDA (bendamustine hydrochloride) for Injection is supplied in individual cartons as follows: NDC 63459-390-08 TREANDA (bendamustine hydrochloride) for Injection, 25 mg in 8 mL amber singleuse vial and NDC 63459-391-20 TREANDA (bendamustine hydrochloride) for Injection, 100 mg in 20 mL amber single-use vial. Storage. TREANDA may be stored up to 25Â°C (77Â°F) with excursions permitted up to 30Â°C (86Â°F) (see USP Controlled Room Temperature). Retain in original package until time of use to protect from light. 50

Distributed by: Cephalon, Inc. Frazer, PA 19355 TREANDA is a trademark of Cephalon, Inc., or its affiliates. All rights reserved. ÂŠ2008-2012 Cephalon, Inc., or its affiliates. TRE-2500 TRE-2511b (Label Code: 00016287.06) This brief summary is based on TRE-2527 TREANDAfull fullPrescribing PrescribingInformation. Information. TRE-006 TREANDA

April 2012 August

Conference News

New Approach for Predicting Treatment-Related Side Effects Phoebe Starr

esearchers are evaluating the use of a cluster of single-nucleotide polymorphisms (SNPs) identified by a Bayesian method from an individual cancer patient to predict the occurrence of treatmentrelated side effects in that patient. Two unpublished studies have shown that SNPs identified by the Bayesian method have an accuracy of more than 90% in predicting treatment-related side effects, explained Stephen Sonis, MD, Brigham and Women’s Hospital, Boston, Massachusetts. Sonis presented preliminary data from the SNP project at the recent meeting of the Multinational Association of Supportive Care in Cancer in New York City. “We believe this [method] will…let us prospectively evaluate and understand who is at risk for side effects from cancer therapy. This can have a major impact on… how we optimize outcomes for our patients,” he stated. SNPs are the most common variation in the genome and outnumber genes exponentially, with over 10 million SNPs and only 25,000 genes. SNPs are not necessarily associated with function, he explained. Using the Bayesian method to analyze 1 million to 2 million individual SNPs and their interactions, it is possible to pick the ones that are relevant. There is no predetermined number of relevant SNPs, or “team players,” as he called them. At Dana-Farber Cancer Center, a retrospective study used Bayesian networks to identify 82 SNPs that were able to predict patients who would develop mucositis with 90% accuracy. The investigators examined charts of myeloma patients slated for transplant from 2001-

2006 and identified 153 subjects; classified them as oral mucositis (OM)-negative (n=102) and OM-positive (n=51), with positivity defined as having 2 consecutive days of WHO grade >2 OM; and extracted DNA from their saliva specimens.

SNPs are the most common variation in the genome and outnumber genes exponentially, with over 10 million SNPs and only 25,000 genes. SNPs are not necessarily associated with function. The investigators then moved on to other cancer types in the OnPART study, which is currently being conducted at the West Clinic in Memphis, Tennessee. This study attempts to use the same method to identify relevant SNPs from individual patients with breast, colorectal, ovarian, and non–small cell lung cancer who are being treated with 3 or more cycles of chemotherapy. Preliminary data in 30 breast cancer patients treated with anthracycline/taxane chemotherapy showed that the rates of side effects were nausea/vomiting, 42%; OM, 38%; diarrhea, 20%; fatigue, 58%; cognitive dysfunction, 23%; and peripheral neuropathy, 16%. The accuracy of prediction using a preselected network of SNPs was 96.7%. Sonis said the data are consistent with the first study in transplant patients with myeloma conducted at Dana-Farber. u

THIRD ANNUAL CONFERENCE Influencing the Patient-Impact Factor

May 2-5, 2013 Westin Diplomat Hollywood, Florida

WWW.PERSONALIZEDMEDONC.COM

September 2012

Interview With the Innovators

Novel Approaches to Delivering Personalized Medicine: An Interview With Thomas C. Reynolds, MD, PhD Thomas C. Reynolds, MD, PhD Chief Medical Officer Seattle Genetics

eattle Genetics is a biotechnology company foCurrently, Seattle Genetics has 3 other clinical-stage cused on the development and antibody-drug conjugate (ADC) procommercialization of empowered grams: SGN-75, ASG-5ME, and ASGmonoclonal antibody–based therapies 22ME. In addition, the company has for the treatment of cancer. Their prodstated that over the next 12 months, 3 uct, brentuximab vedotin (Adcetris), additional INDs will be submitted to was granted FDA accelerated approval move preclinical ADC product candiin August 2011 for 2 indications: the dates into the clinic, and multiple other treatment of patients with Hodgkin ADC candidates are in development by lymphoma after failure of autologous collaborators using Seattle Genetics’ stem cell transplant (ASCT) or after ADC technology. Personalized Medicine failure of at least 2 prior multiagent in Oncology had the pleasure of speaking chemotherapy regimens in patients who with the Chief Medical Officer of SeatThomas C. Reynolds, are not ASCT candidates, and the tle Genetics to discuss ADC technolMD, PhD treatment of patients with systemic ogy, finding unique antigens that are anaplastic large cell lymphoma (ALCL) after failure of at common among several cancer types, and Seattle Genetleast 1 prior multiagent chemotherapy regimen. Seattle ics’ approach to personalized medicine. To view the inGenetics is developing Adcetris in collaboration with terview in its entirety, please visit www.Personalized Millennium: The Takeda Oncology Company. MedOnc.com/videolibrary.

PMO How do you define personalized medicine in oncology, particularly as it relates to the treatment of patients with lymphoma? Dr Reynolds Personalized medicine in oncology is matching a patient and their tumor and the stage of their disease with the best available therapy. That may be using molecular markers, pathways, or other considerations, but really trying to give them the best available therapy to maximize their chance for a cure, for longterm survival, and for a great quality of life.

PMO ADC technology is a novel approach to personalized medicine in oncology and translational medicine in that monoclonal antibodies are developed to unique antigens on the surface of cancer cells and linked to toxic drugs. Can you describe how they work? Dr Reynolds An antibody-drug conjugate is just what the name implies, it’s an antibody hooked to drugs through a stable linker. The beauty of this is that it allows us to deliver a very potent cytotoxic molecule and minimize side effects for the patient.

Dr Reynolds joined Seattle Genetics in March 2007 as Chief Medical Officer. Dr Reynolds has more than 15 years of biotechnology drug development experience, from preclinical development through the FDA approval process. Dr Reynolds holds a BA in chemistry from Dartmouth College and an MD as well as a PhD in biophysics from Stanford University.

Volume 1 • No 4

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Interview With the Innovators

We do this by using an antibody that has exquisite sensitivity and specificity for binding to a target on the surface of a cancer cell, in this case CD30 for Adcetris. After binding to its target, the cytotoxic molecules enter and can kill a cancer cell. The drug is inactive as it moves through the bloodstream, looking for its target. It’s designed to minimize toxicity, but once it’s inside the cancer cell, the cell’s machinery clips the link between the antibody and the drug. This is a critical aspect of Seattle Genetics’ technology – utilizing a linker that can hold the drug securely while it’s in the blood but then release it appropriately once it’s in the cancer cell. Once inside the cancer cell, these “smart bombs” basically detonate and kill the cancer cell through apoptosis. What we have here is high specificity for delivering these potent molecules just to the tumor cell and sparing healthy cells. Therefore, we think this is a way to achieve good efficacy and minimize side effects and achieve a good safety profile. PMO In your opinion, is the promise of personalizing cancer treatments occurring for lymphoma patients being managed by community oncologists? Dr Reynolds The promise of personalizing cancer treatments is becoming a reality for community oncologists and has been for some time. There are a number of targeted therapies that are now being used in the community setting and really helping patients every day. I think one of the best examples is Rituxan. It’s a monoclonal antibody that’s been around for a number of years. Oncologists who take care of patients with blood cancers use it every single day. It’s targeted to CD20, and so the community oncologist is aware of what you need to do to determine if CD20 is present. We are developing Adcetris following the same model. Testing for CD30, the target of Adcetris, is available, and community oncologists have access to it and are using it every day to make the diagnosis of Hodgkin lymphoma and other lymphoma types. If CD30 is present on these tumor types, then the patient is potentially a candidate for Adcetris therapy whether through our approved indications or a clinical trial. We think models like this will move quickly into the

Volume 1 • No 4

community practice setting and really allow a good match between available therapeutics and the patient’s disease. PMO What are the advantages of the ADC approach compared with the more conventional approach of developing drugs that target specific molecular pathways involved in the growth and development of a subpopulation of cancer cells? Dr Reynolds ADCs have some unique advantages in the delivery of personalized oncology medicine to patients in need. One of the beauties of ADCs is their unique and exquisite specificity for targeting antigens that are found predominantly on cancer cells. We select targets that are found on the tumor and either not found

The promise of personalizing cancer treatments is becoming a reality for community oncologists and has been for some time. on or found at extremely low levels on normal cells. This has a 2-fold advantage. One, it delivers very high concentrations of an active cytotoxic drug to the tumor in greater amounts than we could if we were just delivering this as an intravenous chemotherapeutic. And second, the healthy tissues in the body are exposed to much lower quantities of the cytotoxic because they lack the marker, they lack the target. Therefore, patients experience is enhanced efficacy and minimized toxicity. We’ve had patients being able to receive Adcetris for over 3 years with a very acceptable quality of life. One patient who has come and talked with us said nobody asks if he has cancer anymore. He’s in a complete remission. He’s taking the drug long-term. I think that’s a testament to the activity of the drug that it is able to keep that cancer from coming back, but also that the side effects are tolerable, and he can go to work, have a family life, and really have a high quality of life. PMO Are there advantages to the ADC approach with respect to drug development costs? Dr Reynolds Antibody-drug conjugates are not in-

WWW.PERSONALIZEDMEDONC.COM

September 2012

Interview With the Innovators

Primary mechanism of action of ADC: targeted delivery of a cytotoxic agent.

expensive drugs to develop. We have worked for over a decade to develop Adcetris. We think we have a really good idea of how to do this efficiently, but there were a number of challenges in bringing together a biologic, an antibody, and a potent cytotoxic agent, orastatin. This is really a hybrid molecule. It is complicated to manufacture and has required us to come up with new regulatory paradigms to work with the FDA and with the European Medicines Agency (EMA) to show them

ADCs are extremely potent, yet they have a very good safety profile. Adcetris has validated this approach and really established a regulatory precedent.

that we can make a uniform, reproducible, quality product that’s safe and efficacious to give to patients. PMO What implications do ADCs have on the treatment of cancer, and what does this mean for patients and physicians?

Volume 1 • No 4

Dr Reynolds ADCs are going to have a profound implication on the treatment of cancer. I think ADCs are part of a renaissance that’s occurring in oncology using targeted therapy in a personalized approach to really maximize patient care for people living with cancer. ADCs are extremely potent, yet they have a very good safety profile. Adcetris has validated this approach and really established a regulatory precedent. There are now over 25 ADCs in clinical development for other oncology applications. Over half of those use our technology. So we’re really pleased that we’ve been able to work with others to enable the development of new molecules that hopefully will help people live longer and better even though they have cancer. PMO Adcetris is the first approved ADC directed to CD30-expressing cells and the first therapeutic advance in Hodgkin lymphoma in 30 years, but it’s also currently being evaluated in clinical trials for other CD30-positive tumors. Is this the model for ADC technology – that is, find a unique antigen that is common among several cancer types that can be targeted by a monoclonal antibody? Dr Reynolds The model for ADC development is to find an antigen that’s unique on a cancer cell but typically not found or found at low levels in normal tissues, and then figure out whether that molecule can be effective and safe when delivered to multiple different tumor types. I think a good example of this model includes Adcetris receiving approval in 2 indications – relapsed Hodgkin lymphoma and systemic ALCL – and then exploring it further through clinical trials in a number of other tumor types that express CD30, including other lymphomas as well as solid tumors. Another example is a program that we’re investigating in the clinic that targets an antigen known as nectin-4. Nectin-4 is found on many different solid tumor types, so the clinical study that we’re running allows anyone who has nectin-4 on the surface of their tumor to enroll. As more and more ADCs move forward and there’s proof of concept in 1 indication, there’s then a desire to look for that antigen or target in many other types of cancers. We believe that this is akin to treating cancer

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Interview With the Innovators

based on the target and not the cell of origin. I think this is a fundamental paradigm shift that can easily be brought out into the community by the use of simple testing to look for these markers on the surface of the cell. Summarizing, once you find proof of concept in terms of efficacy and safety with a given marker in a given tumor type, the race is then on to see whether this also works in all the other tumor types that express that marker. PMO If brentuximab vedotin is approved for cancers other than Hodgkin lymphoma, will this affect pricing of the drug? Dr Reynolds Brentuximab vedotin is priced for its current indications in relapsed Hodgkin lymphoma and ALCL. We are investigating through clinical trials whether it can be safe and efficacious in other tumor types, but it’s premature to speculate on what that might do to the price at that point in the future. PMO Seattle Genetics is testing ADCs directed at other unique antigens, including CD70, AGS-5, nectin4, and CD19, but several of these antigens can be expressed on normal tissues as well. How do the adverse events associated with ADCs compare with those encountered with other forms of personalized medicine in oncology in which drugs are developed against molecular biomarkers found on subpopulations of cancer cells? Dr Reynolds All molecules that we develop for the treatment of cancer have side effects, and we really strive to understand them early in development using preclinical models and models that we’ve run in the lab to try to predict what might happen to people who are exposed to these agents, especially new treatments like ADCs where we just don’t have a long history. We also focus on selecting target antigens with restricted expression profiles and limited expression on normal tissue. We were very fortunate as we developed Adcetris in that we were able to fully characterize its preclinical safety profile, and when we translated that into people, it worked very well and had fewer side effects than we saw in the preclinical models. So we were grateful for that.

Volume 1 • No 4

Many patients can take Adcetris for very long periods of time and have a very acceptable safety profile. There are some patients, as with any drug, who don’t respond well to the drug or may have a side effect that causes them to stop using the drug. I think if you summarize this you’d say that ADCs are like most drugs. They have efficacy – we think more efficacy than many drugs. And they have side effects – we think maybe a little fewer than other types of therapy. PMO Incorporating molecular biomarker profiling into the management plan for all cancer patients is an expensive undertaking. ADC technology appears to circumvent this process because the unique antigens to which the monoclonal antibodies are targeted are pre-

I believe that molecular testing is going to be important, but we need to refine our test methods so that they become more robust and less expensive. sent on cancer cells of a specific type. As a result, will ADC technology result in personalized medicine at a reduced cost to the patient and healthcare system because it doesn’t require molecular biomarker testing for each individual patient? Dr Reynolds ADC technology will be widely deployed into the community at a reasonably cost-effective rate, and the reason is that looking for targets on the surface of the cell is fairly inexpensive. Immunohistochemistry has been a technology that’s widely deployed by pathologists in the community as well as through central labs. It’s been available for over 50 years. It’s simple, it’s reproducible, and it’s relatively inexpensive. So patients, especially in the blood cancer space, often have large panels of markers that are tested for to best characterize their disease and to match it with the available therapy. It’s already being done. I also believe that molecular testing is going to be important, but we need to refine our test methods so that

WWW.PERSONALIZEDMEDONC.COM

September 2012

Interview With the Innovators

Dr Reynolds demonstrates the mechanism of action of ADC technology.

they become more robust and less expensive, so we can get higher throughput and really do our best job matching available therapies as they evolve to patients and their tumor types.

We think we’ve blazed some new ground here. That regulatory pathway has been validated, and we look forward to new molecules being brought forward... PMO One of the challenges oncologists face is the patient who wants a specific therapy despite the fact that he/she tests negative for the biomarker driving that therapy. Does ADC avoid this issue? Dr Reynolds ADCs are very much like other targeted therapies that require pathways or markers. If you don’t have the marker or the pathway, it’s not likely that you’ll maximally benefit from the drug. We think ADCs should be given to people that have the marker on their cell surface. Now, over time we may find that even patients with low levels of marker may benefit from the drug, or that other agents in combination may potentiate the drug and offer new hope to patients who currently don’t have other options.

Volume 1 • No 4

I think we’re going to keep prosecuting the science to find out how best to use these agents, to find out how much of the target you need on the cell surface, and to continue to develop new molecules to new targets so that we can keep helping people who are living every day with cancer. PMO Are there any special regulatory challenges Seattle Genetics faces regarding ADC technology? Dr Reynolds ADC technology has some unique regulatory challenges. We have the first of a new generation of ADCs to go through the FDA and gain approval, not only for 1 indication but for 2 at the same time. One of the major challenges is the marrying of 2 very different types of molecules that have very different regulatory paradigms: a biologic, the antibody component, and the drug linker, which is a small molecule. They’re regulated by different divisions of the FDA. And one thing that was extremely exciting about bringing the ADC forward was to watch those 2 regulatory divisions come together, provide outstanding reviews of the manufacturing, preclinical and clinical data, and come to a common consensus that Adcetris was efficacious and had a tolerable safety profile and should be approved, and approved ahead of its scheduled FDA action date. We think we’ve blazed some new ground here. That regulatory pathway has been validated, and we look forward to new molecules being brought forward to the FDA and across the pond to the EMA for approval to help patients with cancer soon. PMO Education of providers, pharmacists, payers, and patients is vital in achieving personalized medicine. What effort is Seattle Genetics making in educating these stakeholders? Dr Reynolds Seattle Genetics recognizes it is critical to educate our stakeholders in the power and the promise of ADC technology and in how Adcetris might benefit their patients. We have a multipronged approach. One is our commercial team. We have, we think, one of the top-notch sales forces in oncology. They know how to explain the product to physicians and the staff in the office and help them understand which patients may be available on

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Interview With the Innovators

the labeled indication, and then how best to use the drug and to manage those patients. So they are a fountain of information. Second, we have a medical affairs group that is able to answer questions physicians have about other places this drug might be used and how we could do further studies, investigator-sponsored studies, to better understand other uses of Adcetris. Then third, we work with payers through our managed markets group to ensure they understand the benefits of Adcetris and the data that support reimbursement decisions. Those 3 groups work very well together to ensure that every patient who could benefit from Adcetris has access. PMO In the advent of the personalized medicine era, we are seeing collaborations between companies in an effort to bring better, targeted therapy to patients. How important are intercompany collaborations to Seattle Genetics’ mission? Dr Reynolds Intercompany collaborations are mission critical to really fully developing ADC technology to help patients with cancer. I think a good example is the work that we’ve done in licensing our technology to companies that own targets or markers on cells and have strong intellectual property but really need to punch up the antibody to fully benefit patients. An example is our licensing deals with, among others, Genentech, Astellas, and GlaxoSmithKline. Genentech has prosecuted our technology very widely for a number of targets. They have 8 molecules now in the clinic that are using our ADC technology. In fact, at a recent investor event hosted by Genentech’s parent company Roche, patient data from 5 ADC product can-

didates that all use our technology were highlighted, showing objective responses in both hematologic and solid tumors. We expect to see a lot more data coming from our collaborators, and we think it will be another step to affirm the validation that Adcetris has brought to the ADC landscape.

...only 2% to 3% of patients with cancer participate in a clinical trial. We have got to do better than that, and a lot of this is going to come from the community.

PMO Will it still make sense for Seattle Genetics to develop agents that impact only 5% to 10% of a given patient population? Dr Reynolds The community is very important in bringing forward new technologies like ADC to maximally benefit patients with cancer. One of the biggest challenges we face today is that only 2% to 3% of patients with cancer participate in a clinical trial. We have got to do better than that, and a lot of this is going to come from the community. As we develop personal oncology approaches, smaller and smaller patient populations are going to be available for any given, very targeted therapy. So our only way to do this quickly is for the community to educate patients and to make these trials accessible and easy for patients to enroll in, so we can get the data to develop new drugs and to best match these really cutting-edge therapies with the patients whose lives can be extended and improved upon. u

SECOND ANNUAL CONFERENCE Clinical Approaches to Targeted Technologies REGISTER TODAY AT www.globalbiomarkersconsortium.com

Volume 1 • No 4

WWW.PERSONALIZEDMEDONC.COM

October 4-6, 2013 The Seaport Boston Hotel 1 Seaport Lane Boston, MA 02210

September 2012

Clinical Trial Design

Adaptive Clinical Trial Design: From Simple Dose-Finding Trials to Large-Scale Personalized Medicine Trials Fei Ye, PhD; Yu Shyr, PhD Division of Cancer Biostatistics, Department of Biostatistics Vanderbilt University School of Medicine, Nashville, Tennessee

Key Points • The purpose of increasing the use of adaptive trial designs in drug development is to save resources and/or improve the efficiency and effectiveness of clinical trials while minimizing all potential sources of bias in an adaptive trial • It is important to conduct interim monitoring and analyses appropriately • Type I and type II error rates must be carefully controlled in frequentist approaches • The focus of the design and implementation of personalized medicine trials is moving from early-stage trials to confirmatory phase 3 trials • Personalized medicine trials, particularly biomarker trials, are attracting much attention; however, potential challenges exist for certain types of design, including interpretation of a linkage between the biomarker and the clinical end point

Fei Ye, PhD

Yu Shyr, PhD

hile there’s great excitement about the potential of personalized medicine to improve care – particularly in oncology – there’s also

a healthy dose of pessimism regarding the cost of clinical trials needed to bring optimal, targeted therapies to market. While many researchers believe that personalized medicine is the future of drug development and patient care, there is uncertainty about cost: Will attempts to develop personalized medicines push drug development and healthcare costs higher, or, as some researchers believe, will they lower overall healthcare costs once new targeted therapies are proved safe and effective? Although there have been notable successes, the fulfillment of such promises has been inconsistent. So how can investigators best move forward in developing targeted therapies that may spur even higher development costs? One reasonable strategy is to employ adaptive trial designs, which allow for a prospectively planned modification of certain aspect(s) of the trial design at interim stages, aim to improve the effi-

Dr Ye is Assistant Professor of Biostatistics and Center for Quantitative Sciences faculty member at Vanderbilt Ingram Cancer Center, Department of Biostatistics. Dr Shyr is Director, Vanderbilt Center for Quantitative Sciences; Ingram Professor of Cancer Research; and Professor of Biostatistics, Biomedical Informatics, Cancer Biology, and Preventive Medicine at Vanderbilt University School of Medicine.

Volume 1 • No 4

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Clinical Trial Design

ciency of a trial and increase the chance of success, while enhancing investigators’ understanding of the effect of the treatment. Types of design adaptations include modifications of study eligibility criteria, randomization procedure, sample size, primary and secondary end points, treatment allocation, number of interim analyses, dose levels and duration, as well as methods of statistical analysis. Many critical parameters used in planning a trial are estimated based on certain assumptions, such as response rates, standard deviations, and population means, because of an incomplete or inadequate understanding of these elements. Consequently, a trial may fail to achieve its goal when these prespecified estimates or assumptions substantially deviate from the truth. In many cases, investigators have a good understanding of an investigational drug only after the data have been collected and unblinded. It is not uncommon for investigators to discover only then that the dosage was suboptimal or that some arms of the trial proved unnecessary and could have been dropped early in the trial. However, within the structure of a nonadaptive clinical trial design, investigators can do little to address such limitations without harming the validity of the trial. Over the past 20 years, such concerns have stimulated a tremendous effort to improve the efficiency of trial designs. A common theme has been a move toward adaptive designs. Use of the term “adaptive” has a long history in clinical trial literature. Cornfield and colleagues1 proposed an analytic approach for adaptive trials motivated by the 2-armed bandit model,2 which aims to maximize the number of patients assigned to the more promising of 2 treatments. Zelen3 first introduced the concept of the play-the-winner rule for the same purpose. Wei and Durham4 proposed their play-the-winner rule for the randomization procedure in a sequential trial setting as an improvement of Zelen’s design. Today, the umbrella of adaptive design covers many approaches to introducing some degree of flexibility into a trial, ranging from the basic 3+3 phase 1 trial design for dose finding to cutting-edge biomarker adaptive design. The goal is to incorporate learning from running a trial into its

Volume 1 • No 4

later stages, so that the trial design can be corrected or improved when evidence suggests misspecifications have occurred in the trial’s planning phase. Appropriately, the FDA draft guidance on adaptive clinical trials defines an adaptive design clinical study as “a study that includes a prospectively planned opportunity for modification of one or more specified aspects of the study design and hypotheses based on analysis of data (usually interim data) from subjects in the study.”

In many cases, investigators have a good understanding of an investigational drug only after the data have been collected and unblinded.

Adaptive design offers the potential to yield more information about the investigational treatment than would otherwise be feasible within the time and resources allowed for a particular trial. An adaptive design may allow investigators to discontinue the data collection of 1 or more arms when the current cumulated data show ineffective for the arm(s), thereby reducing cost and time spent on treatments that are not promising based on the learn-and-confirm model, without decreasing the useful information gained of the overall trial. In addition, adaptive design trials may improve the understanding of the dose-response relationship using approaches such as continual reassessment method.5,6

Type of Adaptive Designs Some researchers categorize adaptive trial designs based on the rules for adaptations. There are roughly 4 categories: allocation rules, sampling rule, stopping rule, and decision rule. Allocation rules define how patients will be allocated to different arms in a trial. The sampling rule defines how many patients will be enrolled at the next stage. The stopping rule considers when to stop the trial for reasons such as efficacy, futility, harm, or safety. The decision rule refers to design modifications

WWW.PERSONALIZEDMEDONC.COM

September 2012

Clinical Trial Design

that are not covered by the previous 3 rules, including change of end point, trial hypothesis, and statistical analysis plan. The most widely used adaptive design methods include adaptive dose-finding design, adaptive randomization design, sample size reestimation design, group sequential design, adaptive seamless phase 2/3 design, adaptive treatment selection design, and biomarker design. Each of these design methods is described and discussed below.

Due to potential high toxicity of an investigational drug, many phase 1 trials have a very small number of patients at each dose level, particularly in the early stages. Adaptive Dose-Finding Design The simplest form of adaptive dose-finding trials is the 3+3 phase 1 trial design, which is commonly used in phase 1 oncology trials for finding a maximum tolerable dose (MTD). In a 3+3 trial, 3 patients enter the trial and start at a relatively low dose. If no dose-limiting toxicity (DLT) is observed, another 3 patients are added to the trial at a higher dose. If 1 patient in the first cohort experiences DLT, the 3 additional patients are added at the initial dose. If only 1 of the 6 patients experiences DLT, the dose escalation continues to the next higher level. If 2 or more patients experience DLT, the next lower dose is claimed to be the MTD. There are many variations on this type of design, as the 3+3 design can be generalized to m+n designs7 with different numbers of patients treated at each stage, or designs with different numbers of stages and end points. For example, a recently published study on treatment of metastatic melanoma conducted a phase 1 dose-escalation trial involving an m+n design transitioning seamlessly to a phase 2 design with the maximum dose that could be used without causing adverse effects.8 Generally, these approaches are often found to be inefficient and tend to underestimate the MTD, especially

Volume 1 • No 4

when the initial dose is too low, which necessitates large numbers of escalation steps, including several noninformative doses.7 Due to potential high toxicity of an investigational drug, many phase 1 trials have a very small number of patients at each dose level, particularly in the early stages. Such small sample sizes are clearly one of the sources of uncertainty (ie, high false-negative rate) regarding how precisely the toxicity rate at each stage and the MTD are estimated. The continual reassessment method (CRM) was developed to address some of these problems and has drawn much attention. Many variations of CRM have been published and discussed, including both frequentist and Bayesian approaches. Assuming that the DLTs are binary outcome and that there is a monotonic relationship between dose and toxicity, the general idea behind the method is to assume a prior dose-response curve and the estimated dose-response relationship is updated after each patient’s outcome is observed, so that each patient’s dose is based on the cumulative information about how previously enrolled patients tolerated the drug. In a Bayesian framework, the prior curve represents the investigator’s prior knowledge about the dose response, and the accumulating information from previously enrolled patients can be constructed into the likelihood function. The resulting posterior probability will be the estimate of dose-response curve. This allows the investigators to optimize the trial by means of the adaptation to the cumulative data of an ongoing trial in a Bayesian framework. Compared with the conventional 3+3 design, the Bayesian CRM estimates the MTD more accurately, as it assigns more patients near MTD. Two possible downsides to the Bayesian CRM are: 1) it can increase the computational complexity, and 2) it can escalate doses too quickly. Several modified approaches have been developed in an attempt to overcome these problems. In addition to CRM designs, Ji’s design and modified Ji’s design, both Bayesian approaches, are also commonly used. More complicated adaptive dose-finding designs include designs for general monotonic response, and designs for U-shaped dose response are also available.

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Clinical Trial Design

Example: Adaptive Trials for Dose-Finding Considering Both Efficacy and Safety Two years ago, Berry and colleagues9 introduced their 2-stage adaptive dose-finding trial design with a Bayesian framework. The purpose of this design is to evaluate both efficacy and safety of an investigational drug at possible multiple doses. Initially, patients were randomized equally to 1 of the 4 arms: placebo, active control, treatment at a low dose, and treatment at a medium dose. The maximum number of patients allowed to enter stage I is 240. Based on evidence of efficacy and safety estimated using dose-response models, a decision will be made at each interim analysis to either terminate the trial or move to the second stage. If the trial moves to the second stage, a number of additional doses will be assessed. Patients will be allocated to placebo, treatment at up to 4 different dose levels (very low, low, medium, high), or proportionally to active control in an attempt to achieve equal allocation to all remaining arms at the end of the trial. Enrollment in the high-dose treatment arm depends on the observed toxicities during stage I, and enrollment in the very lowdose treatment arm depends on the observed efficacy from the low-dose treatment arm. The enrollment of stage II patients will continue to the number of the total sample size of the trial (N=500) if not all treatment arms were dropped. In the actual trial, the trial was terminated by the end of stage I after entering 199 patients based on the predictive probabilities that the low/medium treatment arm performs better than the control. One limitation of this trial design mentioned by the authors is that the highest dose is not evaluated at the beginning of the trial because of a relatively narrow prespecified dose range, limiting the potential efficiency gains with a fully responsive-adaptive design. Adaptive Randomization Design Adaptive randomization allows a design to modify randomization schedules by adjusting the probability of assigning patients to treatment groups based on the accumulated data of previously enrolled patients. Common types of adaptive randomization designs include

Volume 1 â&#x20AC;˘ No 4

treatment-adaptive randomization, covariate-adaptive randomization, and outcome-adaptive randomization. Treatment-adaptive randomization aims to achieve a more balanced treatment assignment by tuning the current allocation ratio between treatment arms. The most commonly used approaches include block randomization and the biased-coin method. Covariate-adaptive randomization adjusts the probability of assigning patients to any particular group based on the balance situation of 1 or more important covariates between treatment groups. One widely applied method is mini-

Treatment-adaptive randomization aims to achieve a more balanced treatment assignment by tuning the current allocation ratio between treatment arms. mization randomization, which improves the trialâ&#x20AC;&#x2122;s statistical power but may cause bias since the investigator may be able to decode the randomization schedule. Outcome-adaptive randomization designs assign patients to treatment groups based on response of previous patients. One well-known method is the play-the-winner rule, which involves a dichotomous process. If the outcome of the previous patient is a success, then the same treatment will be assigned to the next patient; otherwise the patient will be assigned the other treatment. This strategy may not be feasible for trials in a disease with a relatively long response time because the next patient assignment depends on the outcome of the previous patients. A randomized play-the-winner rule was proposed to overcome the drawback of the long deterministic process by allocating patients. Although outcome-adaptive randomization could increase the likelihood of success, it has the limitation that the investigator may be able to guess the next treatment assignment based on current response rates, thereby biasing conclusions. In addition, there is the possibility that the patient allocation patterns could change over the course of the trial, when the trial is not effectively blinded, because of the

WWW.PERSONALIZEDMEDONC.COM

September 2012

Clinical Trial Design

knowledge that the randomization is favoring the treatment arm. Block stratification is used to minimize the bias and unbalanced allocation, especially if the trial is not placebo controlled. In a recent of the Journal of Clinical Oncology, there is an interesting ongoing discussion about whether the advantages of outcome-adaptive randomization overweigh its disadvantages or vice versa.10,11

Unblinded sample size reestimation adjusts the sample size at interim analyses based on unblinded interim results or other factors such as external information. Sample Size Reestimation Design In a nonadaptive setting, the sample size is planned prior to the implementation of a trial and is a fixed element. However, it is well recognized that estimation of sample size in clinical trials involve knowledge of treatment effect and variability, which are usually unknown at the planning stage of the trial. The basic idea behind sample size reestimation design is to preserve the statistical power in case of misspecification of the treatment effect or variance to avoid an underpowered trial or oversized trial. The sample size reestimation design allows for recalculating the required sample size based on the accumulating data at interim analyses, either with or without unblinding. Blinded sample size reestimation uses interim data without unblinding treatment assignment to provide an updated estimate of a nuisance parameter, usually the variance for continuous outcomes or the underlying event rate for binary outcomes, so that the required sample size can be adjusted based on the estimate. The number of such adjustments (usually once) and at what time points the interim analysis will be performed should be prespecified. Unblinded sample size reestimation adjusts the sample size at interim analyses based on unblinded interim results or other factors such as external information. It should be noted that the observed difference at interim analyses is often based on a small number of patients. Since sample size calculation

Volume 1 â&#x20AC;˘ No 4

is very sensitive to the effect size used, and treatment effect sizes at interim analyses can be highly variable, sample size estimation at interim stage may be unreliable and can be misleading. Group Sequential Design Group sequential design offers opportunities for early termination of a trial for either safety or efficacy reasons, allowing the sample size to be reduced. At each interim stage, all the accumulated data up to that point are analyzed, and a decision is made whether the trial is stopped or continued. Such decisions are made at interim analyses, and various stopping rules are available in the literature. Most methods attempt to control the overall type I error rate and to terminate the trial when there is neither enough beneficial treatment effect nor sufficient efficacy observed, using approaches such as alpha-spending rules.12-15 If the implementation of a group sequential trial involves unblinding the interim results and analyzing the interim treatment effect, it can raise concerns of potential bias. The FDA recommends that the analyses be carried out either externally to the trialâ&#x20AC;&#x2122;s sponsor or by a group within the sponsor that is unequivocally separated from all other parties to the trial. In addition, some group sequential design approaches may not be able to control the overall type I error rate if the target patient population has been shifted due to additional adaptations or protocol amendments. Adaptive Treatment Selection Designs Play-the-Winner As previously mentioned, the play-the-winner rule uses a simple probability model to randomize patients sequentially to the treatment arm(s). The first patient is randomly assigned to either treatment, with subsequent treatment assignments based on the response of the first patient; the next patient will be assigned to the treatment arm having the highest empirical rate. Play-the-winner approaches are used with the expectation that they would be statistically and ethically superior to simple randomization in the sense that more patients are treated with the better treatment at the end of the trial (based on the ac-

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Clinical Trial Design

cumulated data in a particular trial). However, without sufficient safety data and a carefully developed statistical analysis plan, it is possible to assign more patients to a treatment that is more efficacious but also more toxic. Drop-the-Loser Similarly, a drop-the-loser design involves carrying out an interim analysis and drop 1 or more arms that are not promising, so that more patients can be assigned to better treatments.16,17 It also allows dropping ineffective or high-toxicity treatment arm(s) and therefore may be in the interest of patient safety. The drop-the-loser design is often used to narrow the treatment arms or multiple doses with 2 stages. At the end of the first stage, the inferior arms/doses will be dropped, and the remaining arms/doses will proceed to the second stage. In practice, a 2-stage drop-the-loser trial is usually powered for the second stage, so there may not be sufficient statistical power for the interim analysis performed at the end of the first stage. Precision analysis (confidence interval calculations) is often used to make the decision of dropping the losers. Treatment Switching Another type of adaptive treatment selection design allows the patient to switch from one treatment arm to another based on prognosis and/or investigator’s judgment, often for safety or efficacy reasons. Most commonly, patients switch from the control arm to the intervention arm if there is lack of responses. In cancer trials, a switch may also occur when a patient’s disease progresses to a more severe grade, spurring a shift to an alternative treatment as a last resort. Statistical analysis of such trials may be a challenge because of the complexity caused by treatment switching. For example, patient survival rate will be very difficult to estimate when a large portion of patients switch to the other treatment. Treatment switching may also lead to a change in study hypotheses. Example: Adaptive Treatment Allocation A trial was conducted at the MD Anderson Cancer

Volume 1 • No 4

Center in the 1990s to study troxacitabine-based regimens as induction therapy in the treatment of acute myeloid leukemias.18 Initially, 75 patients were randomly assigned to 1 of 3 treatment arms at the following dosages: idarubicin 12 mg/m2 IV daily for 3 days and araC 1.5 g/m2 IV over 2 hours daily for 3 days versus troxacitabine 6 mg/m2 IV daily for 5 days and ara-C 1 g/m2

In cancer trials, a switch may also occur when a patient’s disease progresses to a more severe grade, spurring a shift to an alternative treatment as a last resort. IV over 2 hours daily for 5 days versus troxacitabine 4 mg/m2 IV daily for 5 days and idarubicin 9 mg/m2 IV daily for 3 days with equal assigning probabilities (ie, P=1/3). The assigning probability of patients to treatment is adjusted based on the accumulated outcome responses (ie, complete response without nonhematologic grade 4 toxicity by 50 days) of patients previously enrolled in favor of arms that demonstrated better performance. This outcome-dependent randomization trial was designed in the spirit of the drop-the-loser rule. More specifically, a treatment arm will be dropped from the randomization if, at any time, the probability that the arm had a shorter time to response than the control or that the other treatment arm is greater than some prespecified threshold. In the actual trial, arm 3 (troxacitabine/idarubicin) was dropped after treating 24 patients and observing the response of 21 other patients, because the control outperformed both arms (response rate: 56% for control, 43% for arm 1, and 0% for arm 2). The assignment probability for the 25th patient was 0.87 to the control and 0.13 to arm 1. Arm 1 was also dropped later after 34 patients had been treated, so the trial was stopped (response rate: 56% for control, 27% for arm 1, and 0% for arm 2). This trial used a Bayesian adaptive randomization framework in which the assigning probability is adjusted in favor of more promising treatment arms. Although both investigational treat-

WWW.PERSONALIZEDMEDONC.COM

September 2012

Clinical Trial Design

ments were rejected by the end of the trial, by using the adaptive design the investigators were able to reach the same conclusions with fewer patients exposed to risks (34 in the adaptive trial vs 75 if a frequentist design had been used). One limitation of this design is that the analysis of some important prognostic covariates may not have sufficient statistical power due to the imbalance as a result of flexible assigning probability.

The decision of whether to stop early, continue to phase 2, or proceed to phase 3 may be made repeatedly rather than at a single decision at 1 time point. Adaptive Seamless Phase 2/3 Design An adaptive seamless phase 2/3 design is a 2-stage design consisting of a learning phase (similar to a phase 2b trial) and a confirmatory phase (phase 3) in a single trial without suspending patient accrual. The term “seamless” indicates that there is no trial suspension between phase 2 and phase 3, with interim analyses for dose selection or futility stop after an initial dose-ranging trial. The decision of whether to stop early, continue to phase 2, or proceed to phase 3 may be made repeatedly rather than at a single decision at 1 time point. Adaptations at the interim analyses may involve different aspects, including treatment selection, sample size reassessment, and stopping for futility. A typical approach is to plan the power of a seamless phase 2/3 trial for the confirmatory phase and use data collected from the learning phase to estimate certainty about the treatment effect using a confidence interval approach. The data collected from both phases are used in the final analysis, which improves the efficiency because fewer patients are needed to obtain about the same information as could be gathered from separate traditional phase 2 and 3 trials. The overall type I error rate is controlled at a prespecified level regardless of the adaptation performed at interim. Such flexibility allows the use of

Volume 1 • No 4

Bayesian methods for interim analyses without affecting the frequentist significance level. Practical aspects concerning the planning and implementation of these adaptive trials have been discussed in the literature.19,20 Bayesian Designs A Bayesian framework that incorporates uncertainty into a parameter in a quantitative manner (ie, expressed by a prior distribution on the parameter) is becoming more common in adaptive trials. The term “adaptive” is not always synonymous with Bayesian, of course, but with more complex adaptive trial designs, many times a Bayesian approach is useful. Instead of estimating the likelihood that an observed response to the investigational treatment could have happened by chance with a frequentist approach, a Bayesian design calculates a predictive probability of treatment efficacy and makes inferences based on the currently available data. In other words, the Bayesian approach continuously learns about the treatment efficacy as data accumulate and updates the posterior probability. The Bayesian approach can be used in many types of adaptations. In dose-finding phase 1 trials, a Bayesian alternative to the 3+3 MTD finding is the Bayesian CRM design. A wellknown Bayesian adaptive dose-response trial is Pfizer’s ASTIN trial in acute stroke.21 Some conservative hybrid designs also exist, with a short 3+3 phase to constrain the dose-response curve before switching to the full CRM design.22 The Bayesian adaptive seamless phase 2/3 design has also attracted great interest. For example, recently a seamless phase 2/3 oncology trial design was proposed to use Bayesian approach to select a sensitive patient population for the development of a targeted therapy.23 In addition to these 2 most commonly applied fields, the Bayesian framework has also been used in outcome-adaptive randomization to model joint efficacy and toxicity outcomes or to select the best treatment for a subgroup of patients based on their prognostic factors with multicourse treatment strategies. Also, a new approach was proposed to reduce the required sample size for a group-sequential survival trial using the Bayesian adaptive model selection strategy.24

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Clinical Trial Design

As mentioned, one of the most attractive features of the Bayesian approach is its ability to incorporate historical data or prior knowledge into the design. It is very important that we carefully choose an appropriate prior distribution for parameters of interest. Some researchers choose noninformative priors to avoid creating a design too sensitive to the prior information. However, such a design does not take existing information into consideration, and noninformative priors may cause the design to be oversensitive to early results. One alternative is to weigh less on the prior by raising the term in the posterior density concerning the prior data to a power that is less than 1 so that the prior does not overly dominate inference, which is necessary when the prior is based on rather limited historical data. To assess frequentist characteristics such as type I and type II error rates of a Bayesian design, an intensive simulation study that considers a wide range of possible scenarios should be carried out. The main purpose is to evaluate how robust and reliable the Bayesian design is under different circumstances, especially when compared with a standard frequentist design. Example: Sample Size Reestimation Phase 2 Design With a Bayesian Framework An adaptive phase 2 design using Bayesian predictive probability and Simon’s minimax design criterion was proposed by Lee and Liu in 2008.25 The design method calculates a predictive probability based on the investigator’s prior knowledge of the treatment’s efficacy and information collected on the current patients at the treatment of each additional patient enrolled after treating the first 10 patients. After the first 10 patients, an interim decision will be made at any interim time, based on the estimated efficacy and toxicity of the treatment. The authors illustrated the design method in 2 examples. Assuming a beta-distributed prior distribution of the response rate and a binomial distribution of the observed number of responses, the predictive probability calculated from the beta-binomial posterior distribution is used to decide whether the trial should be stopped early for either efficacy or futility reasons. Given the

Volume 1 • No 4

same design parameters, type I and type II error rate constraints, and maximum sample size, based on a simulation study, the expected sample size required for the Bayesian design is smaller compared with Simon’s minimax design. Although in certain situations the expected sample size of the Bayesian design is larger than Simon’s optimal design for a given maximum sample size, this design method provides opportunities to modify the number of stages and sample sizes, while allowing continuous monitoring of the outcome.

One of the most attractive features of the Bayesian approach is its ability to incorporate historical data or prior knowledge into the design.

Into the Biomarker-Trial Era In conventional medical care, the regimen is usually guided by standards of care based on results of large cohort studies. However, these large cohort studies do not take into account the genetic variability of individuals or subgroups within a population. Increasingly, investigators are asking if they can improve the outcome (eg, patient survival) by personalizing the regimen to treat each patient more effectively. Trials using dynamic treatment regimens can be viewed as a stream of personalized medicine designs by allowing treatment to vary with time based on individual prognostic factors26,27 or ongoing individual response.17,28 Recently, due to the rapid development of advanced technologies in a number of molecular profiling areas, including proteomic profiling, metabolic analysis, genetic testing, and high-throughput deep sequencing, biomarker-adaptive design has quickly evolved, allowing for a greater degree and broader range of personalized medicine. Biomarkers can be used as intermediate end points to identify target patient populations that are most sensitive to a particular treatment (ie, separate good- and poor-prognosis patients), to predict patients’ responses to a treatment, to replace the primary clinical

WWW.PERSONALIZEDMEDONC.COM

September 2012

Clinical Trial Design

outcome as a surrogate end point for early disease diagnosis, and to identify novel drug targets. These applications are the major contributors to the development of personalized medicine. Biomarker-adaptive design refers to a trial design where the adaption is made based on the response of 1 or more biomarkers (usually multiple) associated with the disease. Biomarkers have already been used in almost every stage of drug development,

In a biomarker-stratified design, patients are randomly assigned regardless of their biomarker status, but the analysis is stratified by the biomarker status. from compound discovery and preclinical studies through each phase of clinical trials and into postmarketing evaluations. One example is a 3-year phase 1/2 trial launched in 2009 for the treatment of metastatic colorectal cancer using proteomic profiles to predict those patients who will respond to the investigational drug imatinib mesylate. In practice, biomarker adaptation can be combined with other adaptation methods in a clinical trial. The selection of surrogate biomarkers in a clinical trial needs to be carefully justified to ensure the association between biomarkers and clinical outcomes under the investigational drug. Establishing a linkage between a biomarker test and the clinical end point is very important in guiding therapy decisions in personalized medicine, which is usually dependent on the ability to classify patients into distinct subgroups based on their genomic and/or proteomic profiles. Conventional clinical trials not involving biomarker tests only estimate the average treatment effect in the overall target population. In order to evaluate biomarkerguided treatments, several biomarker designs have been proposed, such as biomarker-stratified designs, biomarkerstrategy designs, and enrichment designs. In a biomarkerstratified design, patients are randomly assigned regardless of their biomarker status, but the analysis is stratified by the biomarker status. The biomarker-stratified design es-

Volume 1 â&#x20AC;˘ No 4

timates without bias treatment effects across biomarkerdefined subgroups by maximizing the benefits of randomization. However, in some cases it is believed that the treatment may benefit only patients of certain biomarkerdefined subgroups; therefore, the use of a biomarker-stratified design may not be ethical. In this situation, the biomarker-enrichment design can be used as an alternative to estimate the treatment effect among patients of certain biomarker status. Initially, biomarker profiles are obtained from all participating patients but, based on these profiles, only patients who are believed to benefit from the treatment will remain in the trial. Another biomarker design is the biomarker-strategy design. In this design, patients are randomly assigned either to a biomarker-guided arm or to a control arm that is not biomarker based. Within the biomarker-guided arm, biomarker-positive patients are assigned to the investigational treatment, and biomarker-negative patients, together with patients in the control arm, are given the standard treatment. A drawback of the biomarkerstrategy design is that the observed treatment effect may be diluted by having overlapping on-treatment assignment between the treatment arm and the control arm, consequently reducing the trialâ&#x20AC;&#x2122;s statistical power. Additionally, it may not be easy to interpret a significant observed treatment effect because it may be either that the biomarker is useful in guiding the personalized regimen or that 1 treatment is simply more effective than the other, regardless of the biomarker status.29 Example: Adaptive Biomarker Trials Advances in high-throughput genomic technologies offer opportunities to select sensitive patients in a clinical trial. Freidlin and Simon introduced an adaptive design that incorporates a gene expression classifier of drug sensitivity into a randomized phase 3 design as a possible second stage of the analysis.30 Freidlin, Jiang, and Simon published a follow-up paper in the same journal,31 providing a cross-validation extension of the adaptive signature design. Rather than dividing patients into training set and test set, the new version of the design uses a cross-validation method for gene signature devel-

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Clinical Trial Design

opment and testing and is therefore more efficient. Lee and colleagues32,33 applied an outcome-based adaptive randomization trial design in a 4-arm phase 2 trial that has drawn wide attention in recent years. The goal of the BATTLE (Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination) trial is to establish multiple-biomarker classifiers to guide the treatment of patients with non–small cell lung cancer. Patients were assigned to 1 of 4 biomarker groups based on their status of 4 biomarkers (epidermal growth factor receptor mutation/amplification, KRAS and/or BRAF mutation, vascular endothelial growth factor (VEGF) and/or VEGF receptor expression, and RXR and/or cyclin D1 expression). In the first stage of the trial, the initial group of patients was randomized to receive 1 of 4 treatments. Once sufficient treatment data had been collected, the trial moved to its second, adaptive stage. Based on their biomarker status, the remaining patients were assigned to the treatment arm most likely to result in the best outcome. By assigning patients to a treatment arm that is most likely to benefit them, the trial’s efficiency was increased. Other Adaptations In addition to the adaptation designs mentioned above, other adaptations have been proposed and/or applied in clinical trial design, including hypothesis-adaptive design, adaptive enrollment, and primary end point adaptive design. The common goal is to reduce the time and resources required or to explore a wider range of hypotheses (eg, more doses or treatment arms) and/or in a broader population (eg, more subgroups). In spite of the many advantages, there are certain concerns associated with these approaches, some of which are addressed in the Discussion section.

Discussion Adaptive methods have rapidly emerged as powerful tools for clinical trial design. Researchers are employing adaptive trial design, hoping to improve efficiency and save resources. However, simple use of an adaptive design does not guarantee these benefits. They may be offset by bias, causing an increased overall type I error rate,

Volume 1 • No 4

particularly with an unblinded design. It should be remembered, however, that an adaptive interim analysis may require unblinding the data. Bias can arise from patient or dose selection, early withdrawal, treatment switching, modifications of eligibility criteria, change of end point, failure in establishing clinical relevance with the biomarker, and change of statistical analysis. For example, in a typical play-the-winner adaptive design, the decision made at interim review may not be optimal because a “winner’s” observed interim treatment effect, based on a relatively small sample size by chance, can

As a general rule, steps should be taken when possible to improve the power of the study and to avoid an inflated overall type I error rate. be more favorable than it actually is. On the other hand, at interim review a drop-the-loser adaptive trial has the potential to inflate the type II error rate by leading investigators to make wrong decisions on which treatment arms/doses should be eliminated and which should be reserved. In other adaptive methods, reasons causing bias and the magnitude of such bias are not yet well understood. But, as a general rule, steps should be taken when possible to improve the power of the study and to avoid an inflated overall type I error rate. Some types of adaptation may also result in a totally different trial from that originally planned, in which either the target population has been shifted or there is an inconsistency between the original hypotheses and the analysis actually performed. This can jeopardize the trial’s integrity and can cause difficulties in interpreting results regarding the original questions the trial was intended to answer. Because these problems may have a significant impact on the conclusion’s accuracy and reliability, it is important to consider potential sources of bias when planning and analyzing adaptive trials. In some recently developed trials, typically trials for chronic disease, a biomarker or a surrogate end point is

WWW.PERSONALIZEDMEDONC.COM

September 2012

Clinical Trial Design

used as the end point or is used for the interim analysis to determine the adaptive modification. This strategy has the potential to foster advances in personalized medicine by identifying patient subgroups who are more likely to respond to a certain treatment based on their genetic profiles in addition to their clinical characteristics. If there is uncertainty regarding the biomarker’s

For ethical and budgetary reasons, both researchers and the industry are moving toward generalizing adaptive designs to confirmatory phase 3 trials.

predictive ability for the corresponding clinical end point, however, the use of a surrogate may lead to difficulties for both design and final assessment of treatments. Investigators need to provide analytical validation to ensure that the biomarker’s clinical relevance is reproducible (ie, significant statistical correlation between biomarker and clinical end point) and has acceptable levels of sensitivity and specificity. In other words, it is critical to ensure that a surrogate accurately reflects the true clinical end point.34 Introduction of bias to the trial by using a biomarker surrogate is also a concern because of such uncertainty attached; therefore, statistical adjustments are required to control the type I error rate. Additionally, in many circumstances, especially in complex diseases such as cancer, not all treatment effects can be fully accounted for by a single biomarker. The use of multiple biomarkers for 1 disease, however, may lead to a more comprehensive assessment of treatment effects.

Conclusion The discovery-to-market time of drug development has increased dramatically, but the number of approved new drug products is on the decline. Adaptive design has changed the conduct and implementation of clinical trials. Today’s adaptive designs are intended to shorten

Volume 1 • No 4

the discovery-to-market time without decreasing the information collected, to model and monitor the real-time effectiveness of treatment, and also to personalize treatment based on individual genetic profiles and molecular factors. The number of phase 1 and 2 trials that use an adaptive design has increased rapidly. Even though the development of adaptive designs was focused on phase 3 trials, as well as on seamless phase 2/3 trials, fewer phase 3 trials have employed adaptive designs. Adaptive trial design is more popular in early-stage studies because these designs are most helpful when there is little evidence about the treatment effect, a fact more likely to be true in phase 1 and 2 trials than in phase 3 trials. In addition, the FDA raised concerns about the potential bias resulting from unblinding the data of patient response, which is less likely with phase 1 and 2 trials than with phase 3 trials. Currently, for ethical and budgetary reasons, both researchers and the industry are moving toward generalizing adaptive designs to confirmatory phase 3 trials. In the next 5 years or so, adaptive designs undoubtedly will continue to draw more attention from the FDA, industry, and researchers and will most likely become more mainstream, especially for phase 3 trials. In the near future, the use of biomarker-defined subgroups in large-scale clinical trials will likely increase, particularly in light of advances in biological technologies and the increasing availability of bioinformatics software and computational power. Wise use of adaptive trial design is crucial. In spite of their flexibility and efficiency, concerns remain about the integrity and validity of adaptive trials; challenges remain in the statistical analysis of complex adaptive trials. Both type I and type II error rates must be carefully controlled to account for the bias introduced by adaptation(s) and to ensure sufficient sample size to achieve the desired statistical power. In practice, the FDA recommends examining the consistency of treatment effects between study stages, as well as comparability between patients enrolled before and after the adaptation. As many types of adaptive designs are relatively new to most pharmaceutical and biotechnology companies, the potential exists that modifications based

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Clinical Trial Design

on interim analyses could have a negative effect on a trial that has not been properly monitored and executed. Researchers and industry need detailed regulatory guidelines and intensive discussion concerning the valid use of certain adaptive design methods as well as for development of appropriate statistical methods for analyzing complex adaptive trials. u

Acknowledgments The authors would like to thank Peggy Schuyler for editorial advice. This research was supported in part by the Lung Cancer Special Program of Research Excellence (SPORE) (P50 CA090949), Breast Cancer SPORE (P50 CA098131), GI SPORE (P50 CA095103), and Cancer Center Support Grant (CCSG) (P30 CA068485).

References 1. Cornfield J, Halperin M, Greenhouse SW. An adaptive procedure for sequential clinical trials. J Am Stat Assoc. 1969;64:759-770. 2. Robbins H. Some aspects of the sequential design of experiments. Bull Am Math Society. 1952;58:527-535. 3. Zelen M. Play the winner rule and the controlled clinical trials. J Am Stat Assoc. 1969;64:131-146. 4. Wei LJ, Durham S. The randomized play-the-winner rule in medical trials. J Am Stat Assoc. 1978;73:840-843. 5. O’Quigley J, Pepe M, Fisher L. Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics. 1990;46:33-48. 6. O’Quigley J, Shen LZ. Continual reassessment method: a likelihood approach. Biometrics. 1996;52:673-684. 7. Chang M, Chow SC. Power and sample size for dose response studies. In: Ting N, ed. Dose Finding in Drug Development. New York, NY: Springer; 2006. 8. Flaherty KT, Puzanov I, Kim KB, et al. Inhibition of mutated, activated BRAF in metastatic melanoma. N Engl J Med. 2010;363:809-819. 9. Berry SM, Spinelli W, Littman GS, et al. A Bayesian dose-finding trial with adaptive dose expansion to flexibly assess efficacy and safety of an investigational drug. Clin Trials. 2010;7:121-135. 10. Korn EL, Freidlin B. Outcome-adaptive randomization: is it useful? J Clin Oncol. 2011;29:771-776. 11. Berry DA. Adaptive clinical trials: the promise and the caution. J Clin Oncol. 2011;29:606-609. 12. Burington BE, Emerson SS. Flexible implementations of group sequential

stopping rules using constrained boundaries. Biometrics. 2003;59:770-777. 13. Hughes MD, Freedman LS, Pocock SJ. The impact of stopping rules on heterogeneity of results in overviews of clinical trials. Biometrics. 1992;48:41-53. 14. Jennison C, Turnbull BW. Sequential equivalence testing and repeated confidence intervals, with applications to normal and binary responses. Biometrics. 1993;49:31-43. 15. Lehmacher W, Wassmer G. Adaptive sample size calculations in group sequential trials. Biometrics. 1999;55:1286-1290. 16. Bretz F, Schmidli H, Konig F, et al. Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: general concepts. Biom J. 2006;48:623-634. 17. Murphy SA. An experimental design for the development of adaptive treatment strategies. Stat Med. 2005;24:1455-1481. 18. Giles FJ, Faderl S, Thomas DA, et al. Randomized phase I/II study of troxacitabine combined with cytarabine, idarubicin, or topotecan in patients with refractory myeloid leukemias. J Clin Oncol. 2003;21:1050-1056. 19. Jennison C, Turnbull BW. Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: opportunities and limitations. Biom J. 2006;48:650-655. 20. Emerson SS. Issues in the use of adaptive clinical trial designs. Stat Med. 2006;25:3270-3296. 21. Grieve AP, Krams M. ASTIN: a Bayesian adaptive dose-response trial in acute stroke. Clin Trials. 2005;2:340-351. 22. Yin G, Li Y, Ji Y. Bayesian dose-finding in phase I/II clinical trials using toxicity and efficacy odds ratios. Biometrics. 2006;62:777-784. 23. Brannath W, Zuber E, Branson M, et al. Confirmatory adaptive designs with Bayesian decision tools for a targeted therapy in oncology. Stat Med. 2009;28:1445-1463. 24. Wathen JK, Thall PF. Bayesian adaptive model selection for optimizing group sequential clinical trials. Stat Med. 2008;27:5586-5604. 25. Lee JJ, Liu DD. A predictive probability design for phase II cancer clinical trials. Clin Trials. 2008;5:93-106. 26. Thall PF, Sung HG, Estey EH. Selecting therapeutic strategies based on efficacy and death in multicourse clinical trials. J Am Stat Assoc. 2002; 97:29-39. 27. Ratain MJ, Mick R, Janisch L, et al. Individualized dosing of amonafide based on a pharmacodynamic model incorporating acetylator phenotype and gender. Pharmacogenetics. 1996;6:93-101. 28. Lavori PW, Dawson R. Dynamic treatment regimes: practical design considerations. Clin Trials. 2004;1:9-20. 29. Freidlin B, McShane LM, Korn EL. Randomized clinical trials with biomarkers: design issues. J Natl Cancer Inst. 2010;102:152-160. 30. Freidlin B, Simon R. Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients. Clin Cancer Res. 2005;11:7872-7878. 31. Freidlin B, Jiang W, Simon R. The cross-validated adaptive signature design. Clin Cancer Res. 2010;16:691-698. 32. Lee JJ, Xuemin G, Suyu L. Bayesian adaptive randomization designs for targeted agent development. Clin Trials. 2010;7:584-596. 33. Zhou X, Liu S, Kim ES, et al. Bayesian adaptive design for targeted therapy development in lung cancer – a step toward personalized medicine. Clin Trials. 2008;5:181-193. 34. Prentice RL. Surrogate and mediating endpoints: current status and future directions. J Natl Cancer Inst. 2009;101:216-217.

SECOND ANNUAL CONFERENCE ,

Clinical Approaches to Targeted Technologies

October 4-6, 2013 • The Seaport Boston Hotel • 1 Seaport Lane • Boston, MA 02210

WWW.PERSONALIZEDMEDONC.COM

September 2012

Pushing Your Limits Current activities at www.COEXM.com include:

Scan Here to Register.

To use 2D barcodes, download the ScanLife app: • Text “scan” to 43588 • Go to www.getscanlife.com on your smartphone’s web browser, and select “Download” • Visit the app store for your smartphone

COEKsize71112CE

Myelodysplastic Syndromes

Personalized Therapy in the Management of Myelodysplastic Syndromes (MDS) At the 2012 conference of the Global Biomarkers Consortium, which took place March 9-11, 2012, in Orlando, Florida, Gautam Borthakur, MD, from The University of Texas MD Anderson Cancer Center in Houston, Texas, discussed the use of personalized therapy in the management of MDS.

Key Points • Patients with MDS traditionally have been classified, using the International Prognostic Scoring System (IPSS), into 1 of 4 risk groups: low risk, intermediate-1, intermediate-2, and high risk regarding their likelihood of survival and progression to acute myeloid leukemia (AML) • Patients with MDS whose karyotype shows specific cytogenetic abnormality, ie, a deletion of the long arm of chromosome 5 [del(5q)], have a more favorable prognosis than those without this chromosomal aberration • Studies have shown that patients with del(5q) are especially responsive to treatment with the immunomodulatory drug lenalidomide • Recently, researchers have identified mutations in several genes that predict a worse prognosis for patients than would have been expected using the IPSS • Moving forward, it is expected that genetic information will be used as part of a prognostic scoring system and as predictors of therapeutic responses. This will allow further personalization of the care of patients with MDS

he myelodysplastic syndromes (MDS) are a group of hematopoietic stem cell disorders characterized by ineffective hematopoiesis.1 Interstitial 5q deletions [del(5q)], present in 10% to 15% of patients with MDS, are the most frequent chromosomal abnormalities in MDS.1 MDS progress to acute myeloid leukemia (AML) in about 30% of patients after various intervals from diagnosis and at variable rates.2

Prognostic Stratification The original International Prognostic Scoring System (IPSS) for MDS, published in 1997 and based on information from 816 patients with MDS, has been used to classify patients with primary, untreated MDS into 1 of 4 risk groups: low risk, intermediate-1, intermediate2, and high risk regarding the likelihood of survival and progression to AML (Table 1). In this scoring system, risk is determined by the percentage of bone marrow myeloblasts, cytogenetics, and the number of cytopenias. Karyotypic lesions were divided into 3 categories:

Volume 1 • No 4

Case • A 40-year-old male US Air Force pilot in excellent health • Progressive shortness of breath • Hemoglobin: 7 g/dL • Platelet count: 800,000/μL • Absolute neutrophil count: 4000/μL • Vitamin B12 levels: borderline low • Started on vitamin B12 injections; hemoglobin improved to 8 g/dL but no further • Bone marrow metaphase analysis – 11/20 metaphases showed del5 (q13q33)

good [normal, del(5q), del(20q), and –Y], poor (≥3 abnormalities and chromosome 7 anomalies), and intermediate (remaining abnormalities). Cytopenias were defined as a hemoglobin level <10 g/dL, an absolute neutrophil count (ANC) <1500/μL, and a platelet count <100,000/μL. Using this scoring system, patients

WWW.PERSONALIZEDMEDONC.COM

September 2012

Myelodysplastic Syndromes

Table 1. 1997 International Prognostic Scoring System for Patients With Primary, Untreated Myelodysplastic Syndromes3 Prognostic Variable

0.5

Bone marrow myeloblasts (%)

5-10

Karyotype* Number of cytopenias†

Score 1.0 –

Good Intermediate Poor 0/1

2/3

–

1.5

2.0

11-20

21-30

–

*Karyotypes were classified as good [normal, del(5q), del(20q), and –Y], poor (≥3 abnormalities and chromosome 7 anomalies); or intermediate (remaining abnormalities). †Cytopenias were defined as a hemoglobin level <10 g/dL, an absolute neutrophil count <1500/μL, and a platelet count <100,000/μL.

with lower-risk MDS (ie, low-risk or intermediate-1–risk groups according to the 1997 IPSS) account for approximately 70% of patients with the disease.3 According to the 1997 IPSS, the patient in this case would be classified as low risk, since he had only 1 cytopenia, hemoglobin <10 g/dL, and his karyotype, del(5q), was classified as “good.”

Since the publication of the IPSS in 1997, knowledge concerning the epidemiology and pathobiology of the MDS...has increased substantially. Using this prognostic system, the estimated time to the development of AML was 9.4 years for the low-risk group, 3.3 years for the intermediate-1–risk group, 1.1 years for the intermediate-2–risk group, and 0.2 years for the high-risk group; median survival for the groups were 5.7 years, 3.5 years, 1.2 years, and 0.4 years, respectively (Table 2).3 Since the publication of the IPSS in 1997, knowledge concerning the epidemiology and pathobiology of the MDS, including the prognostic impact of cytogenetic abnormalities, has increased substantially. It is now recognized that the 1997 IPSS oversimplified the true biologic

Volume 1 • No 4

heterogeneity of this group of disorders because it omitted rare abnormalities or combinations of lesions.4 Because of this, new prognostic scoring systems have been proposed. For example, Schanz and colleagues recently published a new comprehensive cytogenetic MDS scoring system based on 2902 patients. In this system, 19 cytogenetic categories were defined and then classified according to 5 prognostic subgroups.5 In addition, a revised IPSS (IPSS-R) has been developed that analyzes MDS patient prognosis more precisely than the initial IPSS by defining 5 rather than the 4 major prognostic categories in the original IPSS and including 5 rather than 3 cytogenetic prognostic subgroups.6 Retained in the IPSS-R are the importance of clinical features, such as cytopenias and percentages of myeloblasts, indicating that although cytogenetics are critical in assessing MDS prognosis and potential for progression to AML, they are only a part of the clinical and laboratory evaluation that determines risk. As with the 1997 IPSS, these newer prognostic systems are applicable only to patients with primary, untreated MDS. However, a research group from the MD Anderson Cancer Center has developed and validated a prognostic scoring system for use in patients with established disease.7,8

Treatment According to the most recent guidelines of the National Comprehensive Cancer Network for the treatment of MDS, the patient’s IPSS risk category is used in making therapeutic decisions. The guidelines recommend, “[patients] with del(5q) chromosomal abnormalities and symptomatic anemia should receive lenalidomide.”9 In 2005, the FDA approved lenalidomide, a novel immunomodulatory agent, for use in patients with transfusion-dependent anemia due to low-risk or intermediate-1–risk MDS associated with del(5q) with or without additional cytogenetic abnormalities. The safety and efficacy of lenalidomide were demonstrated in a singlearm, multicenter study in 148 patients with the del(5q) cytogenetic abnormality with or without additional cytogenetic abnormalities.10 Among the 148 patients, 112

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Myelodysplastic Syndromes

Free of Transfusion (%)

(76%) had a reduced need for red blood cell Table 2. 1997 International Prognostic Scoring System for (RBC) transfusions, and 99 (67%) were Patients With Primary, Untreated Myelodysplastic Syndromes: deemed “transfusion independent,” which Survival and Progression to Acute Myeloid Leukemia3 was defined as the absence of RBC transfuRisk Group sion during any consecutive “rolling” 56 days Low Intermediate-1 Intermediate-2 High (8 weeks) during the treatment period. The Overall score 0 0.5-1.0 1.5-2.0 ≥2.5 median time to response was 4.6 weeks 25% AML progression in the 9.4 3.3 1.1 0.2 (range, 1-49 weeks). In patients who absence of therapy (years) achieved transfusion independence, the meMedian survival in the 5.7 3.5 1.2 0.4 dian rise in hemoglobin was 5.4 g/dL (range, absence of therapy (years) 1.1-11.4 g/dL) from baseline. The duration of RBC transfusion independence is shown in Figure 1. Cytogenetic re- Figure 1. Kaplan-Meier Estimate of the Duration of Independence sponse was assessed by standard From Red-Cell Transfusion10 metaphase analysis before and after treatment in patients with at least 20 100 cells in metaphase that could be eval90 uated in sequential specimens. A com80 plete cytogenetic remission was 70 defined as the absence of cells in 60 metaphase containing any abnormal 50 clone. A partial cytogenetic response 40 was defined as a reduction of at least 30 50% in the proportion of abnormal 20 cells in metaphase after treatment. 10 Among 85 patients who could be eval0 uated for cytogenetic responses, 62 0 10 20 30 40 50 60 70 80 90 100 (73%) had cytogenetic improvement, Week and 38 (45%) had a complete cytoge99 93 88 78 69 63 53 33 9 0 No. at Risk netic remission. The most common From List A, Dewald G, Bennett J, et al. Lenalidomide in the myelodysplastic syngrade 3/4 adverse events were neudrome with chromosome 5q deletion. N Engl J Med. 2006;355:1456-1465. Copyright tropenia (54.7%) and thrombocytope© 2006 Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society. nia (43.9%). These results indicate that lenalidomide can overcome the pathogenic effect of del(5q) in MDS was 41.0 weeks. In patients who achieved transfusion and restore bone marrow balance. independence, the median rise in hemoglobin was 3.2 Lenalidomide was also studied in 214 patients with g/dL (range, 1.0-9.8 g/dL) from baseline. The most comtransfusion-dependent, low-risk, and intermediate-1– 11 mon grade 3/4 adverse events were neutropenia (30%) risk MDS who had karyotypes other than del(5q). Among these 214 patients, 56 (26%) achieved transfuand thrombocytopenia (25%). sion independence after a median of 4.8 weeks of treatThe patient in this case was started on lenalidomide ment. The median duration of transfusion independence 10 mg/day. His ANC and platelet count decreased; his

Volume 1 • No 4

WWW.PERSONALIZEDMEDONC.COM

September 2012

Myelodysplastic Syndromes

Case (cont) • Patient was started on lenalidomide at 10 mg/day • Absolute neutrophil count: 800/μL • Platelet count: 100,000/μL • Hemoglobin: 13 g/dL • Cytogenetics: diploid in 3 months – Fluorescence in situ hybridization negative • After 4.5 years: – Reemergence of 5q– clone (in 7/20 metaphases) – Hemoglobin: 13.5 g/dL – Platelet count: 154/μL

Figure 2. Red Blood Cell Transfusion-Independence (TI) Response for Del(5q) Patients With and Without Thrombocytopenia at Baseline12

100 90

Platelet decline <50% Platelet decline ≥50% P=.01 for platelet decline ≥50% vs <50% regardless of baseline levels

TI Response (%)

70 60

75% 50

58%

40 30

47% 33%

20 10 0

No Baseline Thrombocytopenia (n=106)

Baseline Thrombocytopenia (n=42)

Sekeres MA, Maciejewski JP, Giagounidis AA, et al. Relationship of treatment-related cytopenias and response to lenalidomide in patients with lower-risk myelodysplastic syndromes. J Clin Oncol. 2008;26:5943-5949. Reprinted with permission. © 2008 American Society of Clinical Oncology. All rights reserved.

Volume 1 • No 4

hemoglobin improved. He achieved a complete cytogenetic remission in about 3 months; it was negative by fluorescence in situ hybridization as well. The patient stayed on treatment for about 4.5 years and remained transfusion independent. He actually went back to flying. However, after 4.5 years, the del(5q) returned. His lenalidomide dose was increased to 25 mg/day, and the del(5q) clone size decreased, but the clone never disappeared. Unfortunately, the patient recently returned with full-blown AML with complex cytogenetics in a del(5q) background. Thus, this case illustrates that although lenalidomide is generally effective in patients with low-risk MDS associated with del(5q), it is not curative.

Relationship Between Cytopenias and Response As shown above in the results from the lenalidomide studies, approximately half of MDS patients with del(5q) and approximately one-fourth of those without del(5q) treated with lenalidomide experience significant cytopenias. Sekeres and colleagues investigated whether lenalidomide-induced cytopenias that occur early in the treatment course serve as a surrogate marker of clonal suppression and therefore may be predictive of transfusion independence.12 They analyzed 362 low-risk, transfusion-dependent patients with MDS, with or without the del(5q) abnormality, enrolled in the 2 studies described above to determine whether treatment-related cytopenias are correlated with response to lenalidomide. Results showed that among patients with del(5q), 70% of those whose platelet count decreased by ≥50% achieved transfusion independence, compared with 42% of those whose platelet count remained stable or declined by <50% (P=.01). For patients without baseline thrombocytopenia, 75% of patients who experienced a ≥50% decrease in platelet count achieved transfusion independence, compared with 47% of those whose platelet count remained stable or declined <50%; for patients with baseline thrombocytopenia, the numbers were 58% and 33%, respectively (Figure 2).

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Myelodysplastic Syndromes

Figure 3. Red Blood Cell Transfusion-Independence (TI) Response for Del(5q) Patients With and Without Neutropenia at Baseline12

Volume 1 • No 4

P=.02

P=.75

70 60

82% 50

58%

40 30

51% 63%

20 10

Unraveling Molecular Abnormalities in MDS Although specific karyotypic abnormalities have been linked to MDS for decades, recent findings have demonstrated the importance of mutations within individual genes, focal alterations that are not apparent by standard cytogenetics, and aberrant epigenetic regulation of gene expression.13 Bejar and colleagues used a combination of genomic approaches, including nextgeneration sequencing and mass spectrometry–based genotyping, to identify mutations in samples of bone marrow from 439 patients with MDS. They then examined whether the mutation status for each gene was associated with clinical variables, including specific cytopenias, the proportion of blasts, and overall survival.14 Results showed that somatic point mutations are common in MDS. They identified somatic mutations in 18 genes, including 2, ETV6 and GNAS, that had not previously been reported to be mutated in patients with MDS. A total of 51% of all patients had at least 1 point mutation, including 52% of the patients with normal cytogenetics. Mutations in RUNX1, TP53, and NRAS were most strongly associated with severe thrombocytopenia and an increased proportion of bone marrow blasts. Mutations in 5 genes, TP53, EZH2, ETV6,

ANC decline <75% ANC decline ≥75%

100

TI Response (%)

Among patients without baseline neutropenia, 82% of those whose ANC decreased by ≥75% achieved transfusion independence, compared with 51% whose ANC remained stable or decreased by <75% (P=.02). For patients with baseline neutropenia, treatment-related declines in ANC were not correlated with transfusionindependence response (P=.75). Figure 3 compares patients who developed significant treatment-related neutropenia (ANC decline ≥75%) with those who did not (ANC decline <75%). No relationship between the development of cytopenias and response could be established for lower-risk patients with MDS without del(5q). The authors concluded that a direct cytotoxic effect of lenalidomide specific to the del(5q) clone may be indicative of a transfusion-independence response.

No Baseline Neutropenia (n=88)

Baseline Neutropenia (n=60)

Table 3. Gene Mutations Independently Predictive of Poor Overall Survival in Myelodysplastic Syndromes14 Gene

Hazard Ratio for Death From Any Cause

95% Confidence Interval

TP53

2.48

1.60-3.84

EZH2

2.13

1.36-3.33

ETV6

2.04

1.08-3.86

RUNX1

1.47

1.01-2.15

ASXL1

1.38

1.00-1.89

RUNX1, and ASXL1, were independent prognostic indicators of poor overall survival (Table 3). Nearly onethird of the patients in this study were found to have

WWW.PERSONALIZEDMEDONC.COM

September 2012

Myelodysplastic Syndromes

mutations in 1 or more of the 5 prognostic genes identified. Papaemmanuil and colleagues identified somatic mutations of the gene encoding RNA splicing factor 3B, subunit 1 (SF3B1), a core component of RNA splicing machinery, in patients with MDS. First, they identified 64 somatically acquired point mutations in 9 patients with low-grade myelodysplasia and found recurrent somatically acquired mutations in SF3B1.15 Targeted resequencing of SF3B1 was performed in a cohort of 2087 patients with myeloid or other cancers. Follow-up re-

Due to advancements in technology such as whole genome sequencing, the number of known mutations occurring in MDS is steadily increasing. vealed SF3B1 mutations in 72 of 354 patients (20%) with MDS, with a particularly high frequency (65%) among patients whose disease was characterized by ring sideroblasts. The observed mutations were less deleterious than was expected on the basis of chance, suggesting that the mutated protein retains structural integrity with altered function. Clinically, patients with SF3B1 mutations had fewer cytopenias and longer event-free survival than patients without SF3B1 mutations. In a separate study, they set out to further define the clinical significance of these mutations in patients with MDS, myelodysplastic/myeloproliferative neoplasms (MDS/MPN), or acute AML evolving from MDS.16 Somatic mutations of SF3B1 were found in 150 of 533 patients (28.1%) with MDS, 16 of 83 (19.3%) with MDS/MPN, and 2 of 38 (5.3%) with AML. There was a significant association of SF3B1 mutations with the presence of ring sideroblasts (P<.001) and of mutant allele burden with their proportion (P=.002). The mutant gene had a positive predictive value for ring sideroblasts of 97.7% (95% confidence interval, 93.5%-99.5%). In multivariate analysis including established risk factors, SF3B1 mutations were found to be independently asso-

Volume 1 • No 4

ciated with better overall survival (hazard ratio, 0.15; P=.025) and lower risk of evolution into AML (hazard ratio, 0.33; P=.049). The close association between SF3B1 mutations and disease phenotype with ring sideroblasts across MDS and MDS/MPN is consistent with a causal relationship. The authors concluded that SF3B1 mutations are independent predictors of favorable clinical outcome, and their incorporation into stratification systems might improve risk assessment in MDS.

Conclusion/Future Directions Both cytogenetic changes and gene mutations play important roles in the pathogenesis of MDS. Patients with del(5q) have a more favorable prognosis than those without this cytogenetic abnormality, and studies have shown that patients with del(5q) are especially responsive to treatment with lenalidomide. Due to advancements in technology such as whole genome sequencing, the number of known mutations occurring in MDS is steadily increasing.17 Mutations such as TP53, EZH2, ETV6, RUNX1, and ASXL1 have an adverse impact on patient overall survival. SF3B1 mutations, on the other hand, are independent predictors of favorable clinical outcome. Early evidence suggests that specific alterations present in individual patients with MDS can predict prognosis and response to therapy. Bejar and colleagues recently stated, “Elucidation of the full complement of genetic causes of MDS promises profound insight into the biology of the disease, improved classification and prognostic scoring schemes, and the potential for novel targeted therapies with molecular predictors of response.”13 u

References 1. Giagounidis AA, Germing U, Aul C. Biological and prognostic significance of chromosome 5q deletions in myeloid malignancies. Clin Cancer Res. 2006;12:5-10. 2. National Cancer Institute. Myelodysplastic Syndromes Treatment (PDQ®). General information about myelodysplastic syndromes. www. cancer.gov/cancertopics/pdq/treatment/myelodysplastic/HealthProfes sional/page1. Accessed August 23, 2012. 3. Greenberg P, Cox C, LeBeau MM, et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood. 1997;89: 2079-2088. 4. Sekeres MA. Myelodysplastic syndromes: it is all in the genes. J Clin Oncol. 2012;30:774-776. 5. Schanz J, Tüchler H, Solé F, et al. New comprehensive cytogenetic scoring system for primary myelodysplastic syndromes (MDS) and oligoblastic

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Myelodysplastic Syndromes

acute myeloid leukemia after MDS derived from an international database merge. J Clin Oncol. 2012;30:820-829. 6. Greenberg PL, Tuechler H, Schanz J, et al. Revised International Prognostic Scoring System (IPSS-R) for myelodysplastic syndromes [published online ahead of print June 27, 2012]. Blood. 7. Kantarjian H, O’Brien S, Ravandi F, et al. Proposal for a new risk model in myelodysplastic syndrome that accounts for events not considered in the original International Prognostic Scoring System. Cancer. 2008; 113:1351-1361. 8. Komrokji RS, Corrales-Yepez M, Al Ali N, et al. Validation of the MD Anderson Prognostic Risk Model for patients with myelodysplastic syndrome. Cancer. 2012;118:2659-2664. 9. National Comprehensive Cancer Network. NCCN Guidelines Version 2.2013. Myelodysplastic syndromes. www.nccn.org/professionals/physi cian_gls/pdf/mds.pdf. Accessed August 24, 2012. 10. List A, Dewald G, Bennett J, et al. Lenalidomide in the myelodysplastic syndrome with chromosome 5q deletion. N Engl J Med. 2006;355:1456-1465. 11. Raza A, Reeves JA, Feldman EJ, et al. Phase 2 study of lenalidomide

in transfusion-dependent, low-risk, and intermediate-1 risk myelodysplastic syndromes with karyotypes other than deletion 5q. Blood. 2008;111:86-93. 12. Sekeres MA, Maciejewski JP, Giagounidis AA, et al. Relationship of treatment-related cytopenias and response to lenalidomide in patients with lower-risk myelodysplastic syndromes. J Clin Oncol. 2008;26:5943-5949. 13. Bejar R, Levine R, Ebert BL. Unraveling the molecular pathophysiology of myelodysplastic syndromes. J Clin Oncol. 2011;29:504-515. 14. Bejar R, Stevenson K, Abdel-Wahab O, et al. Clinical effect of point mutations in myelodysplastic syndromes. N Engl J Med. 2011;364:2496-2506. 15. Papaemmanuil E, Cazzola M, Boultwood J, et al. Somatic SF3B1 mutation in myelodysplasia with ring sideroblasts. N Engl J Med. 2011; 365:1384-1395. 16. Malcovati L, Papaemmanuil E, Bowen DT, et al. Clinical significance of SF3B1 mutations in myelodysplastic syndromes and myelodysplastic/ myeloproliferative neoplasms. Blood. 2011;118:6239-6246. 17. Schlegelberger B, Göhring G, Thol F, et al. Update on cytogenetic and molecular changes in myelodysplastic syndromes. Leuk Lymphoma. 2012;53:525-536.

SAVE THE DATE SECOND ANNUAL CONFERENCE

July 26-28, 2013 Hyatt Regency La Jolla at Aventine 3777 La Jolla Village Drive San Diego, California Melanoma • Basal Cell Carcinoma • Cutaneous T-Cell Lymphoma Squamous Cell Carcinoma • Merkel Cell Carcinoma

Volume 1 • No 4

WWW.PERSONALIZEDMEDONC.COM

September 2012

Pharmacogenomics

Pharmacogenomics in Cancer Care: Adding Some Science to the Art of Medicine Navin Pinto, MD; Mark J. Ratain, MD The University of Chicago, Chicago, Illinois

Key Points • Germline pharmacogenomics offers clinicians a mechanism to subclassify patients, rather than diseases, and personalize care • As consumer awareness and scientific inquiry expand in pharmacogenomics, the list of important gene-drug interactions is likely to grow • With the growing body of evidence and the rapidly decreasing cost of genomic assessments, the future of prospective genotyping is “today,” and routine clinical implementation will likely lead to improvements in drug safety as well as efficacy

“The future is to-day.” – William Osler, April 20, 1913

espite increasing publicity, “personalized medrecommend focused genetic testing prior to the initiaicine” is not a new phenomenon in cancer tion of therapy for several agents.1 Since publication of care. Oncologists have long the first drafts of the human genome used criteria such as body size, perforin 2001,2,3 our knowledge of the role of mance status, comorbid conditions, inherited, common genetic variation organ function, lifestyle, and a patient’s across the genome in both drug regoals of care to individualize treatment sponse and toxicity has increased exdecisions and drug doses. Additionally, ponentially. Coupled with the rapidly dose adjustments of 1 or more agents decreasing cost of genotyping and during the course of treatment based on whole-genome analyses,4 the era of a physician’s knowledge of the toxicity personalized genomics is upon us. profiles of chemotherapies is a common Oncologists are at the forefront of incorporating genetic testing into clinstrategy to tailor a given patient’s treatical care decisions. Sophisticated ment program. Clinically significant Navin Pinto, MD molecular techniques to identify ongene-drug interactions have been cogenic drivers and/or resistance known for decades, and over the past mechanisms within tumors are becoming a part of the several years, the FDA has altered the labeling of certain diagnostic workup and often help guide therapeutic dedrugs, including several used in cancer care, to warn cision making. For example, testing for somatic mutapractitioners of potential gene-drug interactions and to

Dr Pinto is in the department of pediatrics, section of hematology/oncology at the University of Chicago. He participates on the committee for clinical pharmacology and pharmacogenomics at the University of Chicago. Dr Ratain is in the departments of pediatrics and medicine, section of hematology/oncology at the University of Chicago. He is involved in the Center for Personalized Therapeutics at the University of Chicago.

Volume 1 • No 4

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Pharmacogenomics

tions, such as BRAF V600E, BCR-ABL, and EML4ALK, is now commonplace in metastatic melanoma, chronic myeloid leukemia, and non–small cell lung cancer, respectively. The body of data derived from these tests has led to subdivisions of disease, which in turn has helped oncologists select the best therapies for their patients and enabled clinically significant improvements in survival for many of these disease subcategories.5-7 Germline pharmacogenomics offers clinicians a mechanism to subclassify patients (rather than diseases) and personalize care, analogous to the approach of using tumor genomics to guide disease-specific therapy. In an era when adverse drug reactions are a major cause of morbidity and mortality,8 there is an increased patient and regulatory demand to incorporate pharmacogenomics into clinical care as a preventive strategy. Furthermore, when multiple treatment options are available for a given malignancy or for supportive care measures used in oncology, pharmacogenomics may enable selection of the least toxic treatment regimen without compromising overall treatment success. Ever-increasing consumer demand and a growing body of clinical evidence have led to the rise of both commercial and academic organizations offering personalized genomic services. These services offer patients low-cost genomic screening, including customized reports about susceptibility to both disease and adverse drug reactions. These reports will inevitably land on the desks of treating oncologists along with patient requests to use these results to prescribe the safest and most effective treatment plans. Oncologists now have the ability to hone their sharp personalized medical skills with germline genomic information from their patients. In this article, we will use 3 hypothetical case scenarios to illustrate the power of prospective genotyping in selecting the least toxic chemotherapy or supportive care plan, determining the right dose of cytotoxic chemotherapy, and identifying the agent responsible for a given toxicity in a combination chemotherapy plan with overlapping toxicities. We hope to illustrate that the much-lauded future of personalized medicine – incorporating genetic information into clinical care decisions – is today.

Volume 1 • No 4

Case 1 J.Y. is a 45-year-old female with recently diagnosed stage IA (1.3 cm) estrogen receptor–positive (ER+) breast cancer whose status is post lumpectomy and radiation. Her medical history is notable for menopause at age 42 and mild osteopenia. Family history is significant for an aunt diagnosed with ER+ breast cancer at age 57 who experienced severe musculoskeletal pain while on a clinical trial of exemestane. Her current oncologist is recommending an aromatase inhibitor (AI), but the patient is worried about out-of-pocket costs and has concerns about her family history of poor tolerance to aromatase inhibition. She is in your office to discuss the appropriate maintenance hormone therapy, given her family history, and wonders if genetic testing may help in deciding which drug is best. This case illustrates one of the most common pharmacogenomic inquiries in oncology. The selective ER modulator tamoxifen is FDA approved for the treatment and prevention of breast cancer in women of all ages and is the most commonly prescribed therapy for the treatment of ER+ breast cancer worldwide.9,10 Tamoxifen is converted to active metabolites by several cytochrome P450 enzymes, with CYP2D6 playing a dominant role in the creation of 2 of the most potent ER-blocking

Oncologists now have the ability to hone their sharp personalized medical skills with germline genomic information from their patients. metabolites, 4-hydroxytamoxifen and endoxifen.10,11 More than 100 genetic variants of CYP2D6 have been reported, some of which can lead to altered enzymatic function. Algorithms exist to label patients ultrarapid, extensive, intermediate, and poor CYP2D6 metabolizers based on the number of functional alleles, with ultrarapid metabolizers having numerous copies of CYP2D6 and poor metabolizers having 2 nonfunctional alleles.12 Variant CYP2D6 allele frequencies differ by ethnicity,13 but

WWW.PERSONALIZEDMEDONC.COM

September 2012

Pharmacogenomics

between 7% and 21% of the population are intermediate or poor metabolizers of CYP2D6 substrates.14 Although a paucity of prospective data exists, there is retrospective evidence that decreased CYP2D6 function (either due to genetics or concomitant CYP2D6 inhibitors) is associated with increased rates of breast cancer recurrence.15-18 In 2006, based in part on these results, the FDA recommended that the labeling of tamoxifen be changed to include language that CYP2D6 poor metabolizers may have inferior disease control compared with extensive metabolizers. Although prospective genotyping was not recommended in the FDA label, several companies are now offering CYP2D6 genetic testing to patients, and patients are turning to their oncologists for pharmacogenetic advice.

Because of lower cost and less toxicity relative to aromatase inhibitors, tamoxifen remains an important choice for women with breast cancer.

Although recent large retrospective analyses have thrown the association between CYP2D6 genotype and tamoxifen response into question,19,20 controversy surrounds the methods used in at least 1 of these analyses,21 and the preponderance of evidence supports the use of genotyping to assess which patients might best respond to tamoxifen therapy. Because of lower cost and less toxicity relative to AIs, tamoxifen remains an important choice for women with breast cancer.22 While AIs are usually well tolerated, arthralgias occur in about 50% of patients and likely contribute to suboptimal adherence associated with this class of medications.23 Recent genome-wide analyses in patients treated with AIs for early-stage breast cancer have identified variants (single-nucleotide polymorphisms) on chromosome 14 associated with the nearby gene TCL1A, whose expression was associated with severe musculoskeletal adverse events (AEs).24 One could easily take the patient’s concerns about

Volume 1 • No 4

her family history of AEs and increased costs associated with AIs into account and simply prescribe tamoxifen. However, genotyping to determine her CYP2D6 status (ultrarapid, extensive, intermediate, or poor metabolizer) and/or her risk of musculoskeletal AEs from an AI would help to make a more informed decision about the most tolerable regimen.

Case 2 I.S. is a 73-year-old Caucasian male concert pianist with metastatic colorectal cancer. Given the patient’s profession, FOLFIRI (folinic acid, 5-fluorouracil [5-FU], irinotecan) is chosen over FOLFOX (folinic acid, 5-FU, oxaliplatin) chemotherapy because of the risk of oxaliplatin-induced neuropathy. Cycle 1 is complicated by acute diarrhea responsive to atropine and loperamide, grade IV neutropenia complicated by fever and hospital admission, and grade 1 hand-foot syndrome. Since it is unclear which drug is causative for the severe neutropenia, you prescribe a 25% dose reduction of both 5-FU and irinotecan for cycle 2. Although the practice of oncology is primarily based on randomized clinical trials, there are many situations where there are 2 or more appropriate treatment approaches. Thus, oncologists are often left to practice the art of medicine and use patient factors such as lifestyle, performance status, and comorbidities as well as the side effect profile when choosing the right treatment plan for their patients. FOLFIRI and FOLFOX have emerged as the leading options for the treatment of locally advanced or metastatic colorectal cancer, with headto-head comparisons demonstrating similar response rates.25 Despite this, the 2 regimens have distinct toxicity profiles, with peripheral neuropathy attributable to oxaliplatin being one of the most worrisome side effects for FOLFOX and diarrhea attributable to irinotecan as a leading side effect of FOLFIRI. For Case 2, FOLFIRI appears to be the better choice, given our patient’s profession as a concert pianist. The patient is experiencing mild toxicities from both irinotecan (diarrhea) and 5-FU (hand-foot syndrome), but the

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Pharmacogenomics

more severe toxicity of neutropenia is not clearly attributable to 1 drug, given the overlapping toxicities of the agents. Existing pharmacogenetic knowledge on both of these drugs may help in determining the agent responsible for the neutropenia and lead to a more informed dose-reduction strategy. Irinotecan and 5-FU have marked interpatient variability in toxicity, including neutropenia, and have been the subject of intense pharmacogenetic investigation.26,27 Irinotecan is a prodrug hydrolyzed by carboxylesterases to the more potent topoisomerase inhibitor, SN-38, which is in turn inactivated via glucuronidation by UGT1A1.26 Genetic variation within UGT1A1 that reduces enzymatic activity, most notably a 7-TA repeat within the gene promoter (UGT1A1*28), has been associated with interpatient variability in susceptibility to neutropenia at all dose levels of irinotecan.28 Dihydropyrimidine dehydrogenase (DPD, encoded by the gene DPYD) is responsible for more than 80% of 5-FU catabolism, and toxic deaths from 5-FU due to DPD deficiency were first reported nearly 30 years ago.29 The most well-characterized reduced-function variant, DPYD*2A, is found in up to 50% of Europeans with DPD deficiency, but efforts to link additional DPYD genetic variants to functional DPD deficiency have been problematic.30 The FDA has updated the labels of both irinotecan and 5-FU to urge caution in dosing in patients with reduced function of UGT1A1 or DPD, respectively. Had our patient been prospectively genotyped, we may have discovered him to be a heterozygote in DPYD (DPYD*1/*2A) and wild-type at UGT1A1. One could make an educated assumption that poor irinotecan (SN38) metabolism is likely not playing a role in the patientâ&#x20AC;&#x2122;s neutropenia and that reduced DPD function may be to blame. Cycle 2 could proceed with a dose reduction only in the 5-FU, with full-dose irinotecan, allowing the patient to receive maximal therapy.

Case 3 J.N. is a 16-year-old Asian American male with Bprecursor acute lymphoblastic leukemia (ALL). During

Volume 1 â&#x20AC;˘ No 4

induction therapy the patient develops a desquamating rash consistent with Stevens-Johnson syndrome (SJS). This is attributed to allopurinol given as tumor lysis prophylaxis. He requires total parenteral nutrition and a 2week delay in the resumption of his induction therapy. During consolidation therapy, the patient develops high-spiking fevers, vomiting, and lethargy. He is found to be hypotensive and severely pancytopenic in the emergency room. Despite rapid initiation of antibiotic therapy, adequate transfusion support, and aggressive hypotension management, the patient dies 3 days later in the pediatric ICU. Several months later, his family angrily calls, stating that they read that genetics could have predicted the severe side effects he encountered during his therapy. In oncology, where the therapeutic index of the majority of our active agents is quite low, severe adverse drug reactions are not uncommon. They are particularly troublesome in scenarios like Case 3, where the underlying disease is highly curable and the toxicities could have been accurately predicted and prevented with more information.

In oncology, where the therapeutic index of the majority of our active agents is quite low, severe adverse drug reactions are not uncommon. A growing body of evidence is highlighting the role of common genetic variation within the human leukocyte antigen (HLA) loci and susceptibility to severe drug hypersensitivity reactions. Drugs such as carbamazepine and abacavir now carry boxed warnings from the FDA of an extremely increased risk for severe adverse drug reactions (such as SJS) in patients with the variant HLA-B alleles HLAB*1502 and HLAB*5701, respectively.31,32 Similar data exist for one of the most commonly used supportive care agents in hematologic malignancies, allopurinol, which is used to prevent and

WWW.PERSONALIZEDMEDONC.COM

September 2012

Pharmacogenomics

treat tumor lysis syndrome–associated hyperuricemia. Hypersensitivity reactions, although rare, are a potentially fatal side effect from this medication. Recently, the variant HLAB*5801, seen in <1% of Western Europeans but in up to 8% of Southeast Asians, was found to be strongly linked to the development of allopurinolinduced SJS, with a nearly 100-fold increase in the incidence of SJS compared with controls.33 Alternative

One of the barriers to pharmacogenetic implementation has been the physicians’ desire to rapidly initiate treatment.

tumor lysis syndrome management strategies, such as the recombinant urate oxidase (rasburicase), exist and should be utilized in patients found to be at high risk for allopurinol sensitivity. The thiopurines 6-mercaptopurine (6-MP) and 6thioguanine (6-TG) are backbones of curative treatment of ALL. One of the earliest pharmacogenetic associations linked the variability in enzymatic activity of thiopurine methyltransferase (TPMT) to the observed variability in both toxicity and response to the thiopurines.34 Later, genetic variation within TPMT was found to account for the majority of enzymatic variation.35 In patients with 1 reduced-function TPMT allele, 60% will not tolerate full-dose 6-MP, and all patients with 2 reduced-function TPMT alleles will develop severe, life-threatening myelosuppression when exposed to continuous standard-dose 6-MP.36 Based on these findings, the FDA encourages TPMT function testing or TPMT genotyping for patients needing thiopurines, and formal genotype-based dosing guidelines exist.36 Despite these guidelines, most patients with ALL are not typically assessed for TPMT status. This case illustrates the danger of ignoring wellvalidated pharmacogenetic associations linked to life-threatening adverse drug reactions. Prospective genotyping could have revealed variant HLAB and TPMT genotypes in this patient and would likely have

Volume 1 • No 4

saved his life by predicting his risk of either allopurinol hypersensitivity or thiopurine-induced severe myelosuppression. Alternative supportive care measures and chemotherapy dosing strategies based on genotype would have reduced this patient’s risk of AEs without impacting his chance of cure.

Conclusions and Future Directions Oncologists practice a form of personalized medicine that attempts to give the right dose to the right patient largely by using their clinical knowledge of the best evidence and a patient’s goals of therapy to guide the principles of management. Pharmacogenomics will likely never replace this clinical judgment, and while each of the genetic variants described in this article impacts only 1 aspect of pharmacokinetics or pharmacodynamics, pharmacogenetic algorithms that incorporate multiple variants are now emerging in medicine and will inevitably make their way into oncology. Several wellcharacterized – and many less well-characterized – genedrug interactions are becoming more and more evident to the increasingly well-informed patient, and personalized genomic testing is now in the hands of thousands of consumers. As highlighted in this article, oncologists can harness the power of pharmacogenetics in several ways to help their patients select the most appropriate treatment plan, to determine the offending agent in a combination chemotherapy regimen with overlapping toxicity, and to avoid potentially life-threatening adverse drug reactions. Germline variation and its impact on pharmacokinetics, pharmacodynamics, and immunogenicity can help us understand both interpatient variability in toxicity and, in some cases, response to a given drug, just as understanding the tumor’s driving mutation(s) helps clarify the patient’s disease. As consumer awareness and scientific inquiry expand in pharmacogenomics, the list of important gene-drug interactions is likely to grow, and expert opinion on drug and dose selection based on a patient’s genetic makeup will be of the utmost importance. To date, routine clinical pharmacogenetic implementation has been hindered by lack of physician and

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

Pharmacogenomics

patient knowledge on the subject. Specifically, physicians need to know how and where to order pharmacogenetic or genomic testing, as well as be aware of test turnaround timing. With rapid and inexpensive genomic screens accessible to most patients, physicians should educate themselves on the well-validated pharmacogenetic associations in their field and be prepared to make treatment recommendations based not only on a physical examination, but also on a genetic examination. Several centers, including ours, are incorporating prospective genotyping into routine medical care, as well as providing expert opinion portals for providers to access pharmacogenetic information for their patients.37 In oncology, one of the barriers to pharmacogenetic implementation has been the physicians’ desire to rapidly initiate treatment. As evidenced by the cases outlined in this article, prospective genotyping can aid in selecting the appropriate therapy and, in some cases, the appropriate dose. Oncologists should therefore be leading the charge in the call for prospective genotyping so this information is at the ready when we are faced with a new patient. Because randomized, double-blind trials to prospectively test the clinical utility of single variants will be difficult to conduct, evidenced-based pharmacogenetic dosing strategies are likely to be considered only noninferior to conventional approaches, yet still appropriate for clinical implementation.38 Although further validation is needed for many preliminary pharmacogenetic associations, well-performed studies in additional cohorts are coming at a rapid pace, and the list of genedrug associations with actionable strength of evidence is likely to grow in the coming years. With this evergrowing body of evidence and the rapidly decreasing cost of genomic assessments, the future of prospective genotyping is “today,” and routine clinical implementation will likely lead to improvements in drug safety as well as efficacy. u

References 1. Drugs: table of pharmacogenomic biomarkers in drug labels. FDA Web site. www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ ucm083378.htm. Updated August 3, 2012. Accessed September 9, 2012. 2. Lander ES, Linton LM, Birren B, et al; International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature. 2001;409:860-921.

Volume 1 • No 4

3. Venter JC, Adams MD, Myers EW, et al. The sequence of the human genome. Science. 2001;291:1304-1351. 4. Wetterstrand KA. DNA sequencing costs: data from the NHGRI LargeScale Genome Sequencing Program. National Human Genome Research Institute Web site. www.genome.gov/sequencingcosts. Updated May 21, 2012. Accessed September 9, 2012. 5. Sosman JA, Kim KB, Schuchter L, et al. Survival in BRAF V600mutant advanced melanoma treated with vemurafenib. N Engl J Med. 2012;366:707-714. 6. O’Brien SG, Guilhot F, Larson RA, et al; IRIS Investigators. Imatinib compared with interferon and low-dose cytarabine for newly diagnosed chronic-phase chronic myeloid leukemia. N Engl J Med. 2003;348:9941004. 7. Kwak EL, Bang YJ, Camidge DR, et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med. 2010;363:1693-1703. 8. Shepherd G, Mohorn P, Yacoub K, et al. Adverse drug reaction deaths reported in United States vital statistics, 1999-2006. Ann Pharmacother. 2012;46:169-175. 9. de Souza JA, Olopade OI. CYP2D6 genotyping and tamoxifen: an unfinished story in the quest for personalized medicine. Semin Oncol. 2011;38:263-273. 10. Wu X, Hawse JR, Subramaniam M, et al. The tamoxifen metabolite, endoxifen, is a potent antiestrogen that targets estrogen receptor alpha for degradation in breast cancer cells. Cancer Res. 2009;69:1722-1727. 11. Desta Z, Ward BA, Soukhova NV, et al. Comprehensive evaluation of tamoxifen sequential biotransformation by the human cytochrome P450 system in vitro: prominent roles for CYP3A and CYP2D6. J Pharmacol Exp Ther. 2004;310:1062-1075. 12. Owen RP, Sangkuhl K, Klein TE, et al. Cytochrome P450 2D6. Pharmacogenet Genomics. 2009;19:559-562. 13. Bradford LD. CYP2D6 allele frequency in European Caucasians, Asians, Africans and their descendants. Pharmacogenomics. 2002;3:229243. 14. Crews KR, Gaedigk A, Dunnenberger HM, et al; Clinical Pharmacogenetics Implementation Consortium. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for codeine therapy in the context of cytochrome P450 2D6 (CYP2D6) genotype. Clin Pharmacol Ther. 2012;91:321-326. 15. Kelly CM, Juurlink DN, Gomes T, et al. Selective serotonin reuptake inhibitors and breast cancer mortality in women receiving tamoxifen: a population based cohort study. BMJ. 2010;340:c693. 16. Dezentjé VO, van Blijderveen NJ, Gelderblom H, et al. Effect of concomitant CYP2D6 inhibitor use and tamoxifen adherence on breast cancer recurrence in early-stage breast cancer. J Clin Oncol. 2010;28:2423-2429. 17. Lim HS, Ju Lee H, Seok Lee K, et al. Clinical implications of CYP2D6 genotypes predictive of tamoxifen pharmacokinetics in metastatic breast cancer. J Clin Oncol. 2007;25:3837-3845. 18. Schroth W, Goetz MP, Hamann U, et al. Association between CYP2D6 polymorphisms and outcomes among women with early stage breast cancer treated with tamoxifen. JAMA. 2009;302:1429-1436. 19. Regan MM, Leyland-Jones B, Bouzyk M, et al; Breast International Group (BIG) 1-98 Collaborative Group. CYP2D6 genotype and tamoxifen response in postmenopausal women with endocrine-responsive breast cancer: the Breast International Group 1-98 trial. J Natl Cancer Inst. 2012;104:441-451. 20. Rae JM, Drury S, Hayes DF, et al; ATAC trialists. CYP2D6 and UGT2B7 genotype and risk of recurrence in tamoxifen-treated breast cancer patients. J Natl Cancer Inst. 2012;104:452-460. 21. Nakamura Y, Ratain MJ, Cox NJ, et al. Re: CYP2D6 genotype and tamoxifen response in postmenopausal women with endocrine-responsive breast cancer: the Breast International Group 1-98 trial. J Natl Cancer Inst. 2012;104:1264. 22. Winer EP, Hudis C, Burstein HJ, et al. American Society of Clinical Oncology technology assessment on the use of aromatase inhibitors as adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer: status report 2004. J Clin Oncol. 2005;23:619-629. 23. Gaillard S, Stearns V. Aromatase inhibitor-associated bone and musculoskeletal effects: new evidence defining etiology and strategies for management. Breast Cancer Res. 2011;13:205. 24. Ingle JN, Schaid DJ, Goss PE, et al. Genome-wide associations and functional genomic studies of musculoskeletal adverse events in

WWW.PERSONALIZEDMEDONC.COM

September 2012

Pharmacogenomics

women receiving aromatase inhibitors. J Clin Oncol. 2010;28:4674-4682. 25. Colucci G, Gebbia V, Paoletti G, et al; Gruppo Oncologico Dell’Italia Meridionale. Phase III randomized trial of FOLFIRI versus FOLFOX4 in the treatment of advanced colorectal cancer: a multicenter study of the Gruppo Oncologico Dell’Italia Meridionale. J Clin Oncol. 2005;23:48664875. 26. Innocenti F, Ratain MJ. Pharmacogenetics of irinotecan: clinical perspectives on the utility of genotyping. Pharmacogenomics. 2006;7:12111221. 27. van Kuilenburg AB. Dihydropyrimidine dehydrogenase and the efficacy and toxicity of 5-fluorouracil. Eur J Cancer. 2004;40:939-950. 28. Hu ZY, Yu Q, Pei Q, et al. Dose-dependent association between UGT1A1*28 genotype and irinotecan-induced neutropenia: low doses also increase risk. Clin Cancer Res. 2010;16:3832-3842. 29. Tuchman M, Stoeckeler JS, Kiang DT, et al. Familial pyrimidinemia and pyrimidinuria associated with severe fluorouracil toxicity. N Engl J Med. 1985;313:245-249. 30. Yen JL, McLeod HL. Should DPD analysis be required prior to prescribing fluoropyrimidines? Eur J Cancer. 2007;43:1011-1016. 31. Ferrell PB Jr, McLeod HL. Carbamazepine, HLA-B*1502 and risk of Stevens-Johnson syndrome and toxic epidermal necrolysis: US FDA recommendations. Pharmacogenomics. 2008;9:1543-1546. 32. Martin MA, Klein TE, Dong BJ, et al. Clinical Pharmacogenetics Im-

plementation Consortium guidelines for HLA-B genotype and abacavir dosing. Clin Pharmacol Ther. 2012;91:734-738. 33. Somkrua R, Eickman EE, Saokaew S, et al. Association of HLAB*5801 allele and allopurinol-induced Stevens Johnson syndrome and toxic epidermal necrolysis: a systematic review and meta-analysis. BMC Med Genet. 2011;12:118. 34. Lennard L, Van Loon JA, Lilleyman JS, et al. Thiopurine pharmacogenetics in leukemia: correlation of erythrocyte thiopurine methyltransferase activity and 6-thioguanine nucleotide concentrations. Clin Pharmacol Ther. 1987;41:18-25. 35. Otterness D, Szumlanski C, Lennard L, et al. Human thiopurine methyltransferase pharmacogenetics: gene sequence polymorphisms. Clin Pharmacol Ther. 1997;62:60-73. 36. Relling MV, Gardner EE, Sandborn WJ, et al; Clinical Pharmacogenetics Implementation Consortium. Clinical Pharmacogenetics Implementation Consortium guidelines for thiopurine methyltransferase genotype and thiopurine dosing. Clin Pharmacol Ther. 2011;89:387-391. 37. O’Donnell PH, Bush A, Spitz J, et al. The 1200 Patients Project: creating a new medical model system for clinical implementation of pharmacogenomics [published online ahead of print August 29, 2012]. Clin Pharmacol Ther. 38. Altman RB. Pharmacogenomics: “noninferiority” is sufficient for initial implementation. Clin Pharmacol Ther. 2011;89:348-350.

Currently featuring:

Volume 1 • No 4

Deborah Dunsire, MD President and Chief Executive Officer Millennium: The Takeda Oncology Company

Kathy Giusti Founder and Chief Executive Officer Multiple Myeloma Research Foundation Multiple Myeloma Research Consortium

K. Peter Hirth, PhD Chief Executive Officer Plexxikon, Inc.

Kimberly J. Popovits President, Chief Executive Officer Genomic Health, Inc.

PERSONALIZED MEDICINE

ONCOLOGY

September 2012

www.CutaneousMalignancies.com

SAVE THE DATE • JULY 26-28, 2013 SECOND ANNUAL

CONFERENCE CO-CHAIRS SANJIV S. AGARWALA, MD Professor of Medicine Temple University School of Medicine Chief, Oncology & Hematology St. Luke’s Cancer Center Bethlehem, PA STEVEN J. O’DAY, MD Hematology/Oncology Director of Clinical Research Director of Los Angeles Skin Cancer Institute at Beverly Hills Cancer Center Clinical Associate Professor of Medicine USC Keck School of Medicine Adjunct Faculty, John Wayne Cancer Institute Beverly Hills, CA AXEL HAUSCHILD, MD Professor of Dermatology Department of Dermatology University of Kiel Kiel, Germany

Melanoma • Basal Cell Carcinoma • Cutaneous T-Cell Lymphoma Squamous Cell Carcinoma • Merkel Cell Carcinoma

July 26-28, 2013 Hyatt Regency La Jolla at Aventine 3777 La Jolla Village Drive San Diego, California

www.CutaneousMalignancies.com

CARIS TARGET NOW ™ JUST GOT SMARTER

Decode each patient’s tumor — individualize cancer treatment. DNA mutations. Gene copy number variations and rearrangements. RNA. Protein expression. Each part of cancer biology reveals relevant biomarker information. Caris Target Now™ examines them all to illuminate a clearer path through your patients’ treatment options.

NOW REDESIGNED TO BE SMARTER THAN EVER

• • • •

New Select panels for five common tumor types Clinical Trials Connector™ New “small specimen” friendly technologies Faster turnaround time

VISIT:

CarisTargetNow.com

ON-COMPENDIUM DRUG ASSOCIATIONS AND CLINICAL TRIALS

ON- AND OFF-COMPENDIUM DRUG ASSOCIATIONS AND CLINICAL TRIALS

The use of the Caris Target Now service, the use or interpretation of any information provided as part of su s ch servic vice, e, and and/or /or th the e sele selecti ct on of any dr drug ug age agents nts is so solel lelyy at a and within h n th the e disc discret retion ion of the treating physician’s independent medical judgment. The Caris Target Now services are performed by Cariss Li Life fe Sci Scienc ences, es, a CLI CLIA-c A-certifi fied ed lab labora orator toryy oper operati ating ng und under er the U. U.S. S. Cli Clinic nical al Laboratory Amendment Act of 1988 and in compliance with all relevant U.S. state and federal regulations. None off the Ca Caris ris Ta Targe rgett Now Now ser servic vices es hav have e been been re revie viewed wed by th the e Unit United ed Sta States tes Fo Food od and Drug Administration. Persons depicted are models and used for illustrative purposes only. ©2012 Caris Life Sciences an and d affi affilia liates tes.. All ri right ghtss rese reserve rved. d. CT CTN06 N06131 1312PM 2PMO O