23rd Report of the Austrian HIV Cohort Study by AGES

HIV/AIDS IN AUSTRIA 2013

23rd REPORT OF THE AUSTRIAN HIV COHORT STUDY Austrian Agency for Health and Food Safety www.ages.at

FOREWORD

Alois Stöger Bundesminister für Gesundheit Federal Minister for Health Vorwort von Bundesminister Alois Stöger für den Bericht der österreichischen HIV-Kohortenstudie Die HIV-Infektion hat in den letzten Jahrzehnten viel von ihrem Schrecken verloren. Aus einer meist tödlich verlaufenden Erkrankung wurde eine gut behandelbare Infektion. HIV-Infektion und AIDS dürfen dennoch keinesfalls bagatellisiert werden. Nur die Sicherstellung neuester und wirksamster Behandlungsstrategien garantiert den Erkrankten ein weitgehend normales Leben in hoher Qualität. Was in anderen Ländern oft zu einer unüberwindlichen finanziellen Belastung von Patientinnen und Patienten führt, übernimmt in Österreich die solidarische Krankenversicherung. Diagnostik und Therapie sind bei uns weitgehend kostenfrei. Es ist bedauerlich, dass auch heute noch manche HIV-Infizierte und AIDS-Kranke Vorurteilen ausgesetzt sind. Umso wichtiger ist es, dass sich diese Menschen auf das erstklassige österreichische Gesundheitswesen verlassen können und dass unser Gesundheits- und Sozialwesen weiterhin für diese chronische, behandelbare Infektion optimal gerüstet bleibt. In Österreich gibt es – im Gegensatz zu anderen Ländern – keine Meldepflicht für HIV-Infektionen; meldepflichtig ist bei uns nur AIDS. Wie der vorliegende Bericht belegt, hat sich dies nicht als Nachteil erwiesen. Das österreichische HIV-Surveillance-System liefert umfangreiche Daten von hoher Qualität und hohem Detaillierungsgrad, denen auch in der Gesundheitspolitik als Steuerungsinstrument Bedeutung zukommt. Dies ist dem mit großer Akribie im Vorfeld des 6. Deutsch-Österreichischen AIDS Kongresses, welcher im Juni 2013 in Innsbruck stattfinden wird, erstellten Bericht zu entnehmen, in welchem die Autorinnen und Autoren das verfügbare Datenmaterial dankenswerterweise zusammengeführt haben. Den AutorInnen und den MitarbeiterInnen der österreichischen HIV-Behandlungszentren gebührt dafür unsere ganze Anerkennung. Foreword from Federal Minister for Health Alois Stöger for the Austrian HIV-Cohort Study The following report concerning the Austrian HIV Cohort Study proves once more that Austrian living with HIV and AIDS can rely on their health care system. The latest and most effective treatment strategies are to be utilized to guarantee patients a good quality of life. Unlike the high financial burden for patients in other countries, the Austrian social insurance system accepts the incurring costs almost fully. Diagnostics and therapies are largely free of cost. In Austria, as opposed to other countries, HIV-infection is not mandatorily reportable; official reporting is required for AIDS cases only. This has not proven to be a disadvantage. The Austrian HIV-surveillance-system provides extensive data of high quality and a high degree of detail. Such data are also indispensable for public health governance. In the last decades, HIV-infection and AIDS have lost much of their stigmata. Nonetheless, the significance of HIV –infection and AIDS must not be minimized. In anticipation of the 6. German-Austrian AIDS Congress, this is what is to be conveyed through this meticulous report, in which the authors have compiled all the available data. For this, the authors and the co-workers of the Austrian HIV treatment centres receive our due recognition.

INDEX 1.

INTRODUCTION 6

ORGANIZATION OF THE AUSTRIAN HIV COHORT STUDY 9

FUNDING

4. 4.1 4.2 4.3 4.4

COHORT PARTICIPANTS 13 DEFINITION OF COHORT PARTICIPANTS COHORT COLLABORATIONS RECRUITMENT AND FOLLOW-UP OF COHORT PARTICIPANTS PATIENTS CURRENTLY IN CARE 4.4.1 Overall 4.4.2 Number of patients currently on antiretroviral therapy 4.4.3 How many HIV infections are there in Austria?

14 15 15 18 18 19 20

5. HIV/AIDS SURVEILLANCE IN AUSTRIA 23 5.1 GENERAL OVERVIEW (ECDC DATA) 24 5.2 SEX 28 5.3 MODE OF TRANSMISSION 29 5.3.1 All modes of transmission 29 5.3.2 Categories of heterosexually acquired infections 30 5.3.3 Mother-to-child-transmission 32 5.4 AGE 34 5.4.1 Age at time of HIV diagnosis 34 5.4.1.1 All 34 5.4.1.2 Subgroups 34 5.4.2 Age of the patients currently in care 35 5.5 NATIONALITY AND COUNTRY OF BIRTH 37 5.5.1 Overview 37 5.5.2 Nationality: HIV diagnoses between 2010 and 2012 38 5.5.3 Nationality (living participants) 39 5.6 RESIDENCE 40 5.6.1 Population size of area of residence 40 5.6.2 Residence: Federal states 41 5.7 HEALTH INSURANCE 41 5.8 PROVIDERS OF HEALTH CARE 42 5.9 HIV-1 SUBTYPES 42 5.10 STAGE OF HIV DISEASE 44 5.10.1 Lowest ever measured CD4 cell count (patients currently in care) 44 5.10.2 Classification of the patients currently in care according to CDC 44 5.11 „ELITE-CONTROLLERS“ AND „VIREMIA-CONTROLLERS“ 45 5.12 AIDS 46 6. 6.1

DIAGNOSIS OF HIV AND PRESENTATION TO AN HIV CENTRE PRESENTATION TO AN HIV CENTRE

48 50

6.2

PATIENTS DIAGNOSED SINCE 2001 6.2.1 Frequency of early and late diagnoses 6.2.2 Risk factors for an „early“ diagnosis 6.2.3 Risk factors for a „late“ diagnosis 6.2.4 Risk factors for mortality

7. 7.1 7.2 7.3 7.4

CO-INFECTIONS 59 SYPHILIS 7.1.1 Missing values and status post syphilis diagnoses 7.1.2 Active syphilis: prevalence 7.1.3 „Recent“ syphilis infections: incidence TUBERCULOSIS (LAST CONTACT SINCE 1.1.2005) HEPATITIS C (LAST CONTACT SINCE 1.1.2005) HEPATITIS B (LAST CONTACT SINCE 1.1.2005)

60 60 60 61 62 62 63

8. 8.1 8.2 8.3

TRANSMISSION OF DRUG RESISTANT HIV

67 68 69 71

9. 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8

ANTIRETROVIRAL THERAPY (ART)

NUMBER OF PATIENTS WITH RESISTANCE TEST BEFORE HIV THERAPY „RECENT” INFECTION (TIME OF INFECTION KNOWN OR ESTIMATED) UNKNOWN TIME OF INFECTION (NOT “RECENT”)

PATIENTS CURRENTLY IN CARE REGARDING TREATMENT STATUS REGIMENS OF ANTIRETROVIRAL THERAPY ADMINISTERED ANTIRETROVIRAL DRUGS 9.3.1 Use of NRTI 9.3.2 Use of NNRTI 9.3.3 Use of PI 9.3.4 Use of entry-/ fusion inhibitors 9.3.5 Use of integrase inhibitors 9.3.6 Use of commercial preparations 9.3.7 Use of NRTI combinations 9.3.8 Proportion of patients who have received NRTI-, NNRTI- and PI-drugs CD4 CELL COUNTS AT INITIATION OF ART 9.4.1 CD4 cell counts at initiation of ART 9.4.2 Median CD4 count at ART initiation INITIAL THERAPY 9.5.1 Number of persons who started ART in the respective year 9.5.2 Regimens of the initial therapy 9.5.3 Antiretroviral drugs in the initial therapy ART SWITCHES AND INTERRUPTIONS 9.6.1 Switches and interruptions of ART during the first year of treatment 9.6.2 ART switches and interruptions per calendar year 9.6.3 Risk factors for treatment interruptions since 2007 9.6.4 Risk factors for treatment switches since 2007 DRUG DISCONTINUATION WITHIN 2 YEARS OF STARTING A DRUG (SINCE 2007) FREQUENCY OF DRUG DOSING (DATA FROM JULY 2012) 9.8.1 Overview

52 52 54 55 56

74 76 76 78 78 78 78 78 79 79 79 79 80 80 81 82 82 82 83 84 84 85 86 87 88 92 92

9.9

9.8.2 Frequency of virologic failure related to dosing frequency ACCESS TO ANTIRETROVIRAL THERAPY

92 93

13.

GLOSSARY

134

14.

AUSTRIAN HIV COHORT STUDY GROUP 135

10. BENEFITS OF ANTIRETROVIRAL THERAPY 94 10.1 MORTALITY OF PATIENTS WITH AIDS SINCE 1985 96 10.2 MORTALITY IN COMBINATION ART ERA (YEARS 2005-2010) 98 10.2.1 Causes of death 98 10.2.2 Death rate 98 10.3 CD4 CELL COUNTS 100 10.3.1 CD4 cell counts: nadir and most recent 100 10.3.1.1 Overview 100 10.3.1.2 Most recent CD4 cell count by duration of therapy 101 10.3.2 Increase of CD4 cells during ART 102 10.3.2.1 Factors associated with a recent CD4 cell count >500/µl 103 10.3.2.2 Risk factors for a recent CD4 cell count <200/µl on ART 104 10.4 HIV RNA (VIRAL LOAD) 105 10.4.1 Last HIV RNA in the patients currently in care regardless of ART 105 10.4.2 Last HIV RNA of patients on ART 106 10.4.3 Risk factors for viral replication 107 11. RISKS OF ANTIRETROVIRAL THERAPY 109 11.1 DEFINITION OF RESISTANCE UNDER ART 110 11.2 FREQUENCY OF RESISTANCE 111 11.2.1 Frequency of NRTI-associated resistance mutations 111 11.2.1.1 Overview 111 11.2.1.2 Risk factors for the resistance mutation K65R of the RT 112 11.2.2 Frequency of NNRTI-associated resistance mutations 113 11.2.3 Frequency of PI-associated resistance mutations 114 11.2.4 Resistance to single or multiple drug classes 115 11.2.5 Resistance according to demographic characteristics 116 11.2.6 Cumulative resistance related to different time periods of ART initiation 118 11.2.7 Probability of development of resistance 119 11.2.7.1 Any ART regimen 119 11.2.7.2 Any ART regimen and initial ART after January 1, 1997 119 11.2.7.3 Initial ART with 2 NRTI + 1 NNRTI 119 11.2.7.4 Initial ART with 2 NRTI + 1 PI 119 11.2.8 Patients with 3-class-resistance 120 11.2.8.1 3-class-resistance in different populations 120 11.2.8.2 Risk factors for the development of 3-class-resistance 121 11.3 COMORBIDITIES AND COMEDICATION 122 11.3.1 Comorbidities 122 11.3.2 Comedication 123 11.3.3 Comorbidities related to age 124 11.3.4 Comedication related to age 125 11.3.5 Lipid metabolism abnormalities (patients currently in care) 126 12.

SUMMARY

129

INTRODUCTION

1. Introduction At the end of the year 2001, representatives of 5 Austrian HIV treatment centres (AKH Vienna, Otto-Wagner-Hospital Vienna, AKH Linz, LKH Innsbruck and LKH Graz West) have founded the „Austrian HIV Cohort Study (AHIVCOS)“. In 2008, two more centres (LKH Salzburg and LKH Klagenfurt) joined the AHIVCOS. The responsibility for the medical and scientific coordination lies with Robert Zangerle from the Innsbruck Medical University. Aims of the Austrian cohort study are: 1) Optimization of patient management 2) HIV surveillance 3) Research projects A special software, the „HIV Patient Management System (HIP)“ is used in all centres and has replaced the previous HIV data base in 2005. The input of data is done peripherally in the HIV treatment centres which consistently use the data base for clinical care. The input of laboratory findings is mostly done electronically. Apart from nurses and doctors, additional professional groups are involved in data entry in some centres (social workers, psychologists). Before data can be merged, the cohort participants are made anonymous. Therefore, it is cumbersome to identify cohort participants who are/were treated in more than just one treatment centre. This cannot be done by the use of personal data such as initials, birthday or postal code, but with HIV specific data (date of the HIV test, CD4 cell counts etc.).

2. Organization and development of the Austrian HIV cohort study The organization and further development of the HIV cohort study will stay complex, because some goals of the Austrian HIV Cohort Study are also of interest to health authorities and/ or institutions. The Federal Ministry of Health (BMG, section III, Dr. Jean-Paul Klein) is in charge of HIV, whereas some agenda of this responsibility has been shifted to the Agency for Health and Food Safety (AGES). In contrast, patient care has to be provided by the different federal states, and the social insurance companies bear the costs of the HIV medication. The IT departments in the hospitals have to provide the IT hardware as well as the service/ data security. Because of the support of BMG and AGES, the collaboration between the Austrian HIV Cohort Study and the hospitals, especially with the local IT departments (e. g. interfaces between HIP and local IT systems) is legitimized. For IT departments, HIP as an “isolated application” is seen as an additional liability. On the other hand, hospitals have also an interest in the HIV Patient Management System because tasks of quality management and standardization of care can be managed more efficiently by using HIP. The establishment of the HIV Patient Management System is a big advance in the management of patients with HIV/ AIDS („Good Chronic Disease Practice“).

HIV Patient Management System: Designed as a client-server application, the HIV Patient Management System stores its data in a persistent SQL database. The software is based on the model driven architecture paradigm and has been implemented with Microsoft .NET technology. The company DI Heinz Appoyer (now called network vita) was entrusted with the development of the HIV Patient Management System. The required hardware is provided by the local IT departments in the centres. In terms of data protection the programme fully complies with the Austrian data protection act (DSG 2000, valid since 1.1.2000). Access to the data base in the centres is restricted to authorized users only. On the one hand, the HIV Patient Management System fulfils complex tasks for the clinical management of HIV infected patients, and on the other hand it allows queries and analyses to be performed by the users without restrictions. However, to allow both individual patient management and scientific queries is an enormous challenge which scientific HIV cohorts in other countries have not had to deal with. In Austria, there was no acceptance for a purely scientific data base. While for the clinical patient management the focus is on readability of diagnoses and therapies, creation of medical reports, prescriptions (trade names!), print-out of results etc., scientific queries need precise coding and categorization. Furthermore, the optimization of individual patient management requires an ongoing adjustment to the progress of information technology, whereas purely scientific data bases do not have such technological renewal pressure. Special challenges for the HIV Patient Management System are: • Checking of plausibility of the data after entry in the database • Meeting the requirements of both clinical patient management and scientific database • Weak/ overburdened infrastructure in HIV treatment centres

The development of the HIV Patient Management System incorporated the international standard format, the HIV Cohorts Data Exchange Protocol (HICDEP), so that data merging with networks of cohorts like ART-CC, CASCADE and COHERE has been and will be greatly facilitated.

has been and will be greatly facilitated.

Centres of the Austrian Study Centres ofHIV theCohort Austrian HIV Cohort Study

Vienna

Linz



Upper Austria

Lower Austria

Salzburg

Vorarlberg

Innsbruck

Salzburg

Burgenland

Styria

Tyrol

Graz Carinthia

Klagenfurt

3 Financing 3. FUNDING The financing the(AHIVCOS) Austrianwill HIV Cohort until Study (AHIVCOS) secured until The Austrian HIV CohortofStudy be financed September 2013 (seewill alsobe project plan 2010 September 2013 (see also project plan 2010 – 2013). The maintenance and the – 2013). The maintenance and the further development of the HIV Patient Management System (“HIP”) further development of the HIV Patient Management System (“HIP”) as well as as well as the provision of epidemiological reports (e. g. „Cohort report“) are secured with the public sec-the provision of ofepidemiological (e.the g. partners „Cohort report“ ) are secured the tor (AGES, by order the Federal Ministryreports of Health), in the pharmaceutical industry (allwith compapublic sector (AGES, by order of the Federal Ministry of Health) and with partners in nies providing HIV drugs) and the participating hospitals (routine maintenance contracts). the pharmaceutical industry (all companies providing HIV drugs).

COHORT PARTICIPANTS

4. Cohort participants

4.2

4.1 Definition of Cohort participants

Number of patients included in the COHERE projects of the 2013 merger

The Federal Act Concerning the Protection of Personal Data (Datenschutzgesetz 2000 - DSG 2000) (Sect. 46) (1) has acknowledged special purposes of data regarding scientific research and statistics: “For the purpose of scientific or statistical research projects whose goal is not to obtain results in a form relating to specific data subjects [Betroffene], the controller [Auftraggeber] shall have the right to use all data that….are only indirectly personal for the controller.” Although not being a requirement due to the above mentioned legal situation, the Austrian HIV Cohort Study has gained approval of the ethical committees of the HIV treatment centres. With this the Austrian HIV Cohort Study has been ready to join the international network of cohorts like ART-CC, CASCADE and COHERE. Inclusion criteria: • Proof of the HIV infection Exclusion criteria: • Physician’s decision • Patient withholds consent Frequency of the monitoring („Follow-up“): Cohort participants will be examined and findings/ results documented at regular visits (usually every 3 months), therefore no additional costs will arise. Minimal dataset: • Last negative, first positive HIV test, seroconversion illness, AIDS diagnoses, all cases of death • First contact with the HIV centre • Age, gender, mode of transmission of HIV • CD4 count, HIV RNA, co-infections and co-morbidities • Resistances to antiretroviral drugs • Antiretroviral therapies (past and present) Merger of data: • Only indirectly personal data according to the data protection act • Semiannual

A B C D E F G H I J K

4.3

Cohort collaborations

ART-CC CASCADE Late presenter Virological failure in obese HIV-infected patients treated with efavirenzcontaining regimens HIV-controllers Optimal timing for starting cART in ART-naïve HIV-1–infected patients presenting with cryptococcal meningitis. Association of chronic HBV and HCV co-infection with the development of Non-Hodgkin’s Lymphoma in HIV-infected patients Impact of SVR on overall and liver-related survival in hepatitis co-infected patients Hepatocellular carcinoma in HIV patients Optimal treatment strategy for HCV/HIV coinfected individuals Outcomes of four or more class resistance / virological failure of ART in Europe (1894 patients have 2499 viral sequences)

3018 414 2939 1262 2267 9 2283 864 4 622 90

Recruitment and follow-up of cohort participants

A long-standing aim of the Austrian HIV Cohort Study is a wide, voluntary and anonymous capture of HIV infected patients in Austria. So far, 7584 HIV infected patients providing 61034 years of follow-up have been recruited into the cohort study. We assume that there were more than 1909 deaths, but data entry from patients with loss of follow-up or last contact a long time ago is incomplete. Most centres do not have enough resources to enter data retrospectively. Cumulative number of all cohort participants

01.01.2003

OWS Vienna 1652

AKH Vienna 681

463

01.01.2005

1843

897

621

01.01.2007

2047

1154

707

01.01.2009

1800

01.01.2010

2008

01.01.2011

2290

01.01.2012 01.01.2013

2369 2462

Linz

Salzburg Innsbruck

Graz

Klagenfurt

Total

669

187

3652

749

241

4351

805

305

5018

799

212

870

409

102

4192

835

236

910

446

118

4553

1906

842

264

936

470

129

6837

2078 2242

873 897

288 304

956 993

490 521

155 165

7209 7584

Death 1.1.2012 to 30.6.2012 5 6 4 2 3 0 0 20 Before 1.1.2012 808 359 320 24 304 52 6 1873 (79,2%) (18,8%) (21,7%) (37,8%)

(17,6%) (68,2%)

818 / 4650 595 / 873

(18,1%) (28,1%)

248 / 1372 1165 / 4151 / 125 / 2431 / 1645 / 1322

(37,0%) (24,0%)

245 / 662 1168 / 4861

99 457 357 500

(76,2%) (17,4%) (17,4%) (32,1%)

/ 63 / 1835 / 799 / 2826

48 320 139 906

(25,0%) (27,9%) (42,9%) (21,9%)

/ 2052 / 871 / 420 / 2180

(26,8%) (22,2%)

1086 / 4051 327 / 1472 512 243 180 478

(26,2%) (25,0%)

722 / 2760 691 / 2763

Total

0,1 1

0,4 0,5 1

0,6 1

1,9 1

0,4 0,4 1

1,2 1,4 2,7 1

1,3 1

1,1 1

0,1 –0,1

0,3 –0,4 0,4 –0,5

0,5 –0,7

1,6 –2,2

0,4 –0,5 0,4 –0,5

1,0 –1,4 1,2 –1,6 2,1 –3,3

1,1 –1,5

0,9 –1,2

<0,001

<0,001 <0,001

<0,001

<0,001 <0,001

0,020 <0,001 <0,001

<0,001

0,327

Univariable regression OR (95% CI) p-value

818 370 326 27 310 52 6 1909 Frequencies N = 1413 / 5523 (25,6%)

0,9 –1,4 1,1 –1,6 1,8 –3,0

0,4 –0,5 0,3 –0,4

2,2 –3,5

1,1 1,3 2,3 1 0,4 0,3 1 2,8 1

0,1 –0,1

1,1 –1,6

1,3 1

0,1 1

0,6 –0,9

0,7 1

<0,001

<0,001 <0,001

0,221 0,012 <0,001

0,007

<0,001

Model 1 (N = 5523) Multivariable regression* OR (95% CI) p-value

1644 1872 571 277 683 469 159 5675

* adjusted for the variables: CD4 nadir

OWS Vienna AKH Vienna Linz Salzburg Innsbruck Graz Klagenfurt Total Since 1.7.2012 5 5 2 1 3 0 0 16

Total

Variable Demographic characteristics Age <44 years ≥44 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence Missing < 100 000 ≥ 100 000 > 1 million Nationality High prevalence countries Low prevalence countries Stage of disease AIDS Yes No CD4 nadir Missing value < 200 cells/µl 200-349 cells/µl ≥350 cells/µl ART ART use ever Yes No

All centres

OWS Vienna AKH Vienna Linz Salzburg Innsbruck Graz Klagenfurt Total Last contact with HIV treatment centre Since 1.1.2012 to Before 1.7.2012 30.6.2012 1.1.2012 935 112 597 1228 101 543 451 13 107 224 8 45 565 15 103 346 16 107 131 8 20 3880 273 1522

Risk factors for no follow-up in the last 12 months

Persons with residency abroad were excluded from this analysis.

4.4

Number of currently seen patients by residence

Patients currently in care

HIV-centre

4.4.1 Overall Because of the high number of patients with incomplete follow-up, many analyses were done with data of patients with at least one contact to an HIV centre within the previous 6 months (= patients currently in care).

AKH Vienna

Linz

Salzburg

Innsbruck

Graz

Burgenland

Carinthia

129

151

Lower Austria

160

193

376

Upper Austria

407

438

Salzburg

164

203

Styria

318

340

Tyrol

392

399

Vorarlberg

111

112

Vienna

737

979

1740

Salzburg Innsbruck 140 167 190 209 224

368 411 447 483 517 544 547 565

Graz

Klagenfurt

Total

129 161 204 263 287 313 328 346

90 97 100 125 131

1771 2078 2438 2204 2430 3508 3690 3880

Klagenfurt

Total

Foreign/missing

Total

935

1228

451

224

565

346

131

3880

4.4.2

Number of patients currently in care OWS AKH Linz Vienna Vienna 01.01.2003 577 457 240 01.01.2005 665 568 273 01.01.2007 769 690 328 01.01.2009 845 383 01.01.2010 961 401 01.01.2011 896 1039 426 01.01.2012 908 1133 440 01.01.2013 935 1228 451

OWS Vienna

Number of patients currently on antiretroviral therapy

On January 1, 2013, 3597 patients (92.7%) were on antiretroviral therapy in the 7 HIV treatment centres. Of the 283 patients not on treatment on January 1, 2013, 47 had received antiretroviral treatment at an earlier point in time (women who were on ART to prevent mother-to-child transmission, patients who received transient ART during/ after the acute HIV infection, etc).

Number of participants currently receiving antiretroviral therapy

01.01.2003 01.01.2005 01.01.2007 01.01.2009 01.01.2010 01.01.2011 01.01.2012 01.01.2013

OWS Vienna 425 482 594 786 819 883

AKH Vienna 342 421 493 687 799 909 1020 1137

Linz

Salzburg

Innsbruck

Graz

Klagenfurt

Total

178 228 269 306 345 367 394 422

107 140 169 189 199

247 296 347 408 426 462 503 533

86 123 158 217 250 283 287 306

68 79 88 111 117

1278 1550 1861 1793 2039 3064 3323 3597 21

Number of participants currently receiving antiretroviral therapy

Number of participants currently receiving ART regarding federal state HIV-centre OWS Vienna

AKH Vienna

Linz

Salzburg

Innsbruck

Graz

Burgenland

Carinthia

115

131

Lower Austria

153

181

357

Upper Austria

382

410

Salzburg

146

185

Styria

282

301

Tyrol

369

375

Vorarlberg

106

107

Vienna

695

907

1622

Klagenfurt

Total

Foreign/missing

Total

883

1137

422

199

533

306

117

3597

4.4.3

How many HIV infections are there in Austria?

More than 85% of the patients on antiretroviral treatment (ART) in Austria are recruited in the cohort study. Persons with residence in foreign countries have been excluded from this analysis.

AHIVCOS:

Patients on ART (3560)

3560

Patients not on ART (281)

281

Patients lost to follow-up 6-12 months (269)

250 *

Patients lost to follow-up 12-78 months (881)

250 * 440 *

Patients lost to follow-up >78 months (532)

170 *

628

314

1881

2822

7524

8465

Outside AHIVCOS: Patients on ART (628) Patients not on ART (314) Undiagnosed:

Total:

Estimated to be 25-33% of all HIV infections

* Excluded: estimated number of persons who have either left the country or who have deceased

440 *

HIV/AIDS SURVEILLANCE IN AUSTRIA

5. HIV/AIDS Surveillance in Austria 5.1

HIV infections, per 100 000 population, reported for 2011: Heterosexual cases

General overview (ECDC data)

HIV infections, per 100 000 population, reported for 2010: All cases

HIV infections, per 100 000 population, reported for 2011: Men who have sex with men cases

The Austrian HIV Cohort Study has been approved as a surrogate source for reporting of HIV, data from AHIVCOS has been transferred to ECDC on September 14th, 2012.

HIV infections, per 100 000 population, reported for 2011: All cases

5.2 Sex

5.3

Mode of transmission

5.3.1

All modes of transmission

27.8% of the patients with a follow-up within the last 12 months are female. The rate is highest in Upper Austria (35.5%) and Vorarlberg (33.3%). In the subgroup of heterosexually acquired infections, the rate of the women is 51.3%. It is highest in Upper Austria (56.6%), Vienna (52.4%) and Vorarlberg (52.2%).

Year 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Gender of the patients with a follow-up in the last 12 months All

AHIVCOS

BMG

Heterosexually acquired HIV-infection

Total 313 339 428 402 442 423 470 453 435 515 505 507 487 525 523

MSM 80 (33,3%) 73 (30,4%) 73 (30,7%) 76 (26,6%) 88 (28,8%) 80 (27,3%) 87 (26,3%) 89 (27,1%) 127 (39,2%) 126 (37,5%) 154 (43,8%) 131 (44,0%) 158 (50,5%) 146 (48,5%) 132 (46,2%)

27 36 44 58 51 56 67 62 41 51 39 29 31 36 35

IDU (11,3%) (15,0%) (18,5%) (20,3%) (16,7%) (19,1%) (20,2%) (18,9%) (12,7%) (15,2%) (11,1%) (9,7%) (9,9%) (12,0%) (12,2%)

Heterosexually infected 120 (50,0%) 108 (45,0%) 102 (42,9%) 134 (46,9%) 144 (47,1%) 135 (46,1%) 159 (48,0%) 155 (47,3%) 130 (40,1%) 135 (40,2%) 141 (40,1%) 120 (40,3%) 100 (31,9%) 100 (33,2%) 99 (34,6%)

Others 13 (5,4%) 23 (9,6%) 19 (8,0%) 18 (6,3%) 23 (7,5%) 22 (7,5%) 18 (5,4%) 22 (6,7%) 26 (8,0%) 24 (7,1%) 18 (5,1%) 18 (6,0%) 24 (7,7%) 19 (6,3%) 20 (7,0%)

Total 240 240 238 286 306 293 331 328 324 336 352 298 313 301 286

Women 53 (22,1%) 69 (28,8%) 68 (28,6%) 71 (24,8%) 85 (27,8%) 92 (31,4%) 106 (32,0%) 90 (27,4%) 77 (23,8%) 77 (22,9%) 81 (23,0%) 69 (23,2%) 59 (18,8%) 68 (22,6%) 56 (19,6%)

Patients with a follow-up in the last 12 months

The abbreviation MSM is used for „Men who have sex with men”. IDU means „Injecting Drug Use“. The category IDU also includes men who are both MSM and IDU. The category “blood products” includes cohort participants who have received coagulation compounds or blood transfusions. Among the patients with a follow-up in the last 12 months, 41.3% have been infected through heterosexual contacts, 37.7% through homosexual contacts and 15.1% through the injection of drugs.

5.3.2

Categories of transmission

Categories of heterosexually acquired infections

Sub-categories of transmission Women Men

Sub-categories of heterosexually acquired infections

5.3.3 Mother-to-child-transmission Nowadays, mother-to-child-transmission is the only route of HIV transmission amongst children. All HIV infected children in Austria are followed in paediatric HIV treatment centres, therefore the data presented here are related to patients who have also been in care by the adult HIV treatment centres. Obviously, these data are incomplete.

Burgenland Lower Austria Upper Austria Styria Tyrol Vorarlberg Vienna Missing residency Total

Living participants <18 years >18 years 0 1 3 0 5 4 0 2 0 5 4 0 7 8 3 1 22 21

Deceased participants 0 0 1 0 4 1 2 0 8

Recently, at least two transmissions of mother-to-child in Austria have been linked to counselling with HIV denialists.

Total 1 3 10 2 9 5 17 4 51

In January 2010, routine HIV testing was introduced in Austria. The HIV test is part of the mother-child booklet (Mutter-Kind-Pass). In order to be eligible for childcare allowance (Kinderbetreuungsgeld) you must have the first ten examinations stipulated in the mother-child booklet done correctly and obtain proof of it.

5.4

Age

5.4.1

Men (not MSM):

Age at time of HIV diagnosis

5.4.1.1 All Median age at time of the HIV diagnosis

Women:

Women Men

5.4.2 5.4.1.2 Subgroups

MSM:

Age of the patients currently in care

Overall, median age increased from 39.3 in July 2002 to 44.5 in January 2013. In MSM, median age increased from 41.2 in July 2002 to 44.6 in January 2013, in Men (not MSM) from 40.0 to 46.5 and in women from 37.5 to 42.2.

Median and average age are 44.5 and 44.9 years, respectively, and both are very similar across the federal states. 10.2 % are older than 60 years, 31.5% are older than 50 years.

5.5

Nationality and country of birth

5.5.1 Overview

Age at time of the HIV diagnosis

Nationality BMG

Federal states Patients currently in care â&#x20AC;&#x201C; injecting drug use

Year 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Total 313 339 428 402 442 423 470 453 442 515 505 507 487 525 523

Austria 192 80,0% 186 77,5% 179 75,2% 206 72,0% 236 77,1% 197 67,2% 226 68,3% 211 64,3% 203 62,7% 215 64,0% 222 63,1% 199 66,8% 213 68,1% 207 68,8% 191 66,8%

Low prevalence countries 22 9,2% 33 13,8% 27 11,3% 37 12,9% 36 11,8% 41 14,0% 41 12,4% 43 13,1% 50 15,4% 54 16,1% 70 19,9% 51 17,1% 68 21,7% 63 20,9% 57 19,9%

AHIVCOS High prevalence countries Missing value 19 7,9% 7 2,9% 19 7,9% 2 0,8% 32 13,4% 0 0,0% 41 14,3% 2 0,7% 34 11,1% 0 0,0% 54 18,4% 1 0,3% 62 18,7% 2 0,6% 69 21,0% 5 1,5% 61 18,8% 10 3,1% 62 18,5% 5 1,5% 55 15,6% 5 1,4% 48 16,1% 0 0,0% 32 10,2% 0 0,0% 31 10,3% 0 0,0% 38 13,3% 0 0,0%

Total 240 240 238 286 306 293 331 328 324 336 352 298 313 301 286

5.5.2

Nationality: HIV diagnoses between 2010 and 2012

5.5.3

Nationality (living participants)

All

MSM

HIV diagnosis 2010

HIV diagnosis 2011

N=313

N=301

Austria Germany Hungary Romania Slovakia Bosnia and Herzegovina Croatia Serbia Poland Russian Federation Albania Greece Italy England Portugal Switzerland Belarus France Ukraine Macedonia Iran Turkey China Thailand India Indonesia and Timor Macao Georgia Uzbekistan Liberia South Africa Gambia Tanzania Congo USA Cameroon Cote dÂ´Ivoire Ghana Kenya Nigeria Morocco Tunisia Guinea-Bissau Mexico Brazil

213 13 1 8 1 3 2 6 5 3 1 2 4 1 1 1 1 1 1 2 1 1 1 2 1 1 1 2 2 1 1 2 1 1 1 3 1 4 3 7 1 1 1 1 2

Austria Germany Hungary Romania Czech Republic Slovakia Bosnia and Herzegovina Croatia Serbia Poland Russian Federation Italy Belgium England Switzerland Slovenia France Macedonia Turkey China Thailand India Malaysia Gambia Tanzania Zimbabwe Somalia Ghana Kenya Nigeria Rwanda Angola Honduras Brazil Peru St. Vincent , Grenadines

HIV diagnosis 2012 N=286 207 17 5 5 1 1 2 3 2 5 5 2 1 2 2 2 1 1 6 1 5 1 1 1 1 1 3 1 2 7 2 1 1 1 1 1

Estonia Europe Sweden Latvia Germany Austria Bulgaria Hungary Romania Czech Republic Slovakia Bosnia and Herzegovina Croatia Serbia Poland Russian Federation Italy Spain Netherlands Portugal Slovenia Macedonia Iraq Turkey Nepal Thailand Bangladesh Azerbaijan Africa Gambia Congo Ethiopia Cameroon Ghana Kenya Mali Nigeria Senegal Togo Zambia Brazil Chile Venezuela

1 1 1 1 14 191 1 6 4 3 1 1 2 2 1 4 4 1 1 1 2 2 1 1 1 7 1 1 2 1 4 2 2 1 5 1 5 1 1 1 1 1 1

IDU

Heterosexually acquired infection

Low prevalence countries are countries with an HIV infection rate of adults <1%, high prevalence countries are countries with an HIV infection rate of adults â&#x2030;Ľ1%. 41

5.6 Residence 5.6.1

Residence: Federal states

5.7

Health insurance

Population size of area of residence Living with HIV/AIDS < 100 000

Burgenland Carinthia Lower Austria Upper Austria Salzburg Styria Tyrol Vorarlberg Vienna

5.6.2

e 100 000

> 1 million

Deceased < 100 000

e 100 000

> 1 million

N (% women) N (% women) N (% women)

85 120 545 330 103 252 264 130 -

17 13 98 150 17 28 89 73 -

(29,4%) (31,7%) (25,9%) (32,7%) (26,2%) (31,0%) (29,9%) (32,3%)

60 225 132 212 174 -

(20,0%) (39,1%) (20,5%) (23,1%) (28,7%)

2815 (24,7%)

(23,5%) (15,4%) 4 (25,0%) (12,2%) (32,0%) 173 (32,9%) (29,4%) 28 (14,3%) (17,9%) 27 (22,2%) (23,6%) 113 (25,7%) (24,7%) 1043 (19,2%)

Federal state outside capital city (< 100 000)

In the framework of statutory health insurance, all gainfully active persons must become insured. Approximately 99% of the Austrian population are protected by statutory health insurance. Depending on the type of employment there are different kinds of mandatory health insurance: e.g. BVA for civil servants, SVA for businessmen and businesswomen, and GKK for most employees. Providers of health insurance according to the federal state (patients with a follow-up within the last 12 months)

Capital city of federal states (â&#x2030;Ľ 100 000)

5.8

Providers of health care

All patients

Included are patients with a follow-up within the last 12 months. No. of patients Innsbruck 580 Linz 464 Age < 50 665 Age e 50 379 < 100 000 656 e 100 000 388 Total 1044

General practice 456 (78,6%) 265 (57,1%) 433 (65,1%) 288 (76,0%) 473 (72,1%) 248 (63,9%) 721 (69,1%) No. of patients

Innsbruck Linz Patients without ART Patients with ART HIV RNA > 50 (with ART) HIV RNA â&#x2030;¤ 50 (with ART) Chronic hepatitis C Use of antidepressants Women Men MSM IDU Hetero Age < 50 years Age e 50 years < 100 000 inhabitants e 100 000 inhabitants Total

5.9

580 464 70 974 90 882 157 174 328 716 351 168 461 665 379 654 388 1044

Psychiatry 47 18 36 29 43 22 65

(8,1%) (3,9%) (5,4%) (7,7%) (6,6%) (5,7%) (6,2%)

Internal Dermato- PulmonoOthers medicine logy logy 32 (5,5%) 8 (1,4%) 4 (0,7%) 67 (11,6%) 32 (6,9%) 10 (2,2%) 11 (2,4%) 92 (19,8%) 28 (4,2%) 15 (2,3%) 11 (1,7%) 99 (14,9%) 36 (9,5%) 3 (0,8%) 4 (1,1%) 60 (15,8%) 43 (6,6%) 10 (1,5%) 13 (2,0%) 94 (14,3%) 21 (5,4%) 8 (2,1%) 2 (0,5%) 65 (16,8%) 64 (6,1%) 18 (1,7%) 15 (1,4%) 159 (15,2%)

No doctors outside GP, centre no specialist 94 (16,2%) 345 (59,5%) 153 (33,0%) 168 (36,2%) 23 (32,9%) 35 (50,0%) 224 (23,0%) 478 (49,1%) 29 (32,2%) 39 (43,3%) 193 (21,9%) 439 (49,8%) 30 (19,1%) 80 (51,0%) 30 (17,2%) 84 (48,3%) 57 (17,4%) 126 (38,4%) 190 (26,5%) 387 (54,1%) 99 (28,2%) 189 (53,8%) 33 (19,6%) 85 (50,6%) 100 (21,7%) 203 (44,0%) 181 (27,2%) 313 (47,1%) 66 (17,4%) 200 (52,8%) 142 (21,7%) 334 (51,1%) 104 (26,8%) 178 (45,9%) 247 (23,7%) 513 (49,1%)

Specialist, no GP 30 (5,2%) 46 (9,9%) 4 (5,7%) 72 (7,4%) 6 (6,7%) 63 (7,1%) 12 (7,6%) 7 (4,0%) 41 (12,5%) 35 (4,9%) 17 (4,8%) 11 (6,5%) 41 (8,9%) 51 (7,7%) 25 (6,6%) 40 (6,1%) 36 (9,3%) 76 (7,3%)

GP, + specialist 111 (19,1%) 97 (20,9%) 8 (11,4%) 200 (20,5%) 13 (14,4%) 187 (21,2%) 35 (22,3%) 53 (30,5%) 104 (31,7%) 104 (14,5%) 46 (13,1%) 39 (23,2%) 117 (25,4%) 120 (18,0%) 88 (23,2%) 138 (21,1%) 70 (18,0%) 208 (19,9%)

HIV-1 subtypes

Subtypes were determined by genotypic resistance testing of Reverse Transcriptase (RT) and Protease according to Stanford database. Examples of the use of the resistance test in Tyrol and Upper Austria are given in the graphs below. Tyrol

Heterosexually acquired infections

Not heterosexually acquired infections

Upper Austria

5.10 Stage of HIV disease

5.11 „Elite-controllers“ and „viremia-controllers“

5.10.1 Lowest ever measured CD4 cell count (patients currently in care)

Median time from HIV-1 infection to death in untreated patients is estimated to be approximately 10-12 years. However, there is considerable variation in survival time between patients. A small number of patients remain asymptomatic for many years and maintain high CD4 cell counts or low plasma HIV RNA levels, or both, without antiretroviral therapy. Patients able to maintain high CD4 counts have been called “long-term non-progressors”, whilst those with low viral loads have been called “HIV controllers” or “elite controllers”. Viremic controllers have low but readily measurable virus loads. Elite controllers suppress HIV to extremely low levels, measurable only by sensitive laboratory techniques.

The median of the lowest CD4 cell count ever measured („CD4 nadir“) in the patients currently in care is 204/µl.

CD4 nadir (patients currently in care)

Being ART naive All patients

5.10.2 Classification of the patients currently in care according to CDC The classification of the HIV infection according to CDC puts patients in one of three clinical categories (A, B, C) and one of three CD4 cell count categories (1, 2, 3).

CD4 count 1 e 500/µl 2 200-499/µl 3 < 200/µl

A Asymptomatic A1 A2 A3

B Non-AIDS defining conditions B1 B2 B3

C AIDS C1 C2 C3

HIV-infected up to 5 years

HIV-infected for 6 to 10 years

HIV-infected for over 10 years

N = 1282

N = 1021

N = 1815

206 16,1%

3,9%

1,3%

HIV RNA d 50 copies/ml

1,0%

0,9%

0,3%

HIV RNA < 400 copies/ml

1,8%

1,3%

0,7%

HIV RNA < 1000 copies/ml

2,7%

1,3%

0,7%

HIV RNA < 5000 copies/ml

5,0%

1,8%

0,8%

135 10,5%

2,4%

0,8%

CD4 > 500 cells/µl CD4 > 500 cells/µl and HIV RNA d 50 copies/ml

0,6%

0,5%

0,3%

CD4 > 500 cells/µl and HIV RNA < 400 copies/ml

1,1%

0,7%

0,6%

CD4 > 500 cells/µl and HIV RNA < 1000 copies/ml

1,8%

0,7%

0,6%

5.12 AIDS Because most of the AIDS cases have occurred before the use of the HIV Patient Management System and many of these patients have died, the documentation of patients with AIDS is incomplete (exceptions: Tyrol and Upper Austria). AIDS-Statistics:

AHIVCOS

Before 1995 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Total

AIDS cases AHIVCOS

AIDS <6 months after HIV test AHIVCOS

868 164 149 121 126 127 122 103 95 89 87 98 97 108 93 88 79 76 81 2771

40,2% 29,9% 31,5% 38,0% 40,5% 45,7% 38,5% 47,6% 38,9% 48,3% 50,6% 44,9% 41,2% 47,2% 50,5% 47,7% 49,4% 47,4% 51,9% 41,9%

Ministry of health All deaths AHIVCOS

Deaths of AIDS cases AHIVCOS

658 148 100 61 72 63 68 67 56 61 65 81 56 75 59 57 68 58 36 1909

525 122 82 37 48 42 48 51 30 35 42 51 35 50 28 32 39 32 23 1352

Deaths of AIDS cases AIDS cases BMG BMG 1548 245 189 146 162 152 144 121 115 105 106 117 118 129 110 102 94 64 66 3833

974 176 106 50 63 54 68 58 34 40 48 60 40 58 35 38 43 32 19 1996

AIDS-Statistics: AIDS and deaths since January 1st, 2000

Burgenland Carinthia Lower Austria Upper Austria Salzburg Styria Tyrol Vorarlberg Vienna Total

AHIVCOS AIDS <6 months AIDS cases after HIV test AHIVCOS AHIVCOS 13 61,5% 33 78,8% 100 54,0% 162 42,6% 62 64,5% 76 61,8% 85 44,7% 46 58,7% 600 38,0% 1177 47,7%

All deaths AHIVCOS 12 6 58 96 32 43 56 29 461 793

Deaths of AIDS cases AHIVCOS 6 3 32 79 19 24 38 18 268 487

Ministry of health Deaths of AIDS cases AIDS cases BMG BMG 9 19 41 87 21 27 46 27 291 583

DIAGNOSIS OF HIV AND PRESENTATION TO AN HIV CENTRE

6. Diagnosis of HIV and presentation to an HIV centre 6.1

Categories of CD4 cells at time of HIV diagnosis Women

Presentation to an HIV centre

Austria has one of the highest rates of HIV tests in Europe (more than 75 tests per year per 1000 population). Nevertheless, a substantial portion of the patients (>40%) are diagnosed late (CD4 cell count <350/Âľl).

Time between HIV test and first CD4 cell count Year measurement in months (median, percentiles 25, 75, 90) of HIV All patients IDU diagnosis N Months N Months

First CD4 cell count (all patients, 278 missing) Median

Quartiles

1985

314

>12

(all >12)

190

>12

1990

217

>12

(0, >12, >12)

6,1

(0, >12, >12)

235

(47 - 500)

1995

213

1,8

(0, >12, >12)

4,4

(1, >12, >12)

230

(81 - 457)

2000

232

0,7

(0,

10, >12)

1,6

(1, >12, >12)

361 (168 - 554)

2001

281

0,7

(0,

6, >12)

2,0

(1,

8, >12)

356 (167 - 575)

2002

300

0,6

(0,

4, >12)

0,9

(0,

8, >12)

380 (201 - 610)

2003

291

0,6

(0,

3, >12)

1,2

(0,

8, >12)

353 (172 - 539)

2004

327

0,5

(0,

4, >12)

1,6

(0,

9, >12)

356 (162 - 565)

2005

322

0,5

(0,

2, >12)

0,9

(0,

5, >12)

344 (152 - 532)

2006

318

0,6

(0,

3, >12)

1,1

(0,

3, >12)

366 (193 - 571)

2007

327

0,5

(0,

4, >12)

1,0

(0,

5, >12)

321 (160 - 530)

2008

346

0,6

(0,

2, >12)

1,5

(0,

9, >12)

342 (198 - 524)

2009

286

0,5

(0,

10)

0,7

(0,

3, >12)

345 (186 - 534)

2010

304

0,4

(0,

0,5

(0,

8, >12)

389 (192 - 604)

2011

294

0,4

(0,

0,9

(0,

10)

355 (216 - 542)

2012

275

0,3

(0,

0,6

(0,

339 (130 - 551)

316 (119 - 551)

(all >12)

Men

CD4 count at first presentation

6.2

Patients diagnosed since 2001

6.2.1

Frequency of early and late diagnoses

Percentage of patients with late and advanced diagnosis

“Early” diagnosis or „recent“ infection is defined as: acute HIV infection (westernblot pattern or antigen/ HIV RNA combined with clinical presentation) or documented seroconversion with negative HIV test not more than 3 years before the first positive test. “Late” diagnosis is defined as: CD4 cell count below 350 at time of HIV diagnosis and/or AIDS within 3 months of HIV diagnosis “Advanced” diagnosis is defined as: CD4 cell count below 200 at time of HIV diagnosis and/or AIDS within 3 months of HIV diagnosis “Intermediate” diagnosis: CD4 cell count > 200, however not early diagnosed

Diagnosis AIDS within 3 months of testing HIV positive

1,9 0,4 1

26 / 587 (4,4%) 572 / 3167 (18,1%) 501 0 26 71

Low prevalence countries * adjusted for the variables: gender

1,0 1,7

1188 / 2526 (47,0%) 10 / 30 (33,3%) 363 / 587 (61,8%) 611 (49,6%)

1,7 1

363 / 587 (61,8%) 1501 / 3167 (47,4%)

303 /

1,4 1,3 1

/ 53 (45,3%) / 1283 (51,9%) / 525 (49,0%) / 1893 (48,4%)

24 666 257 917

1,3 0,8

1,4 1,2

2,0

1,4

1,2

1,1 1

515 (52,0%) 71 (43,7%)

343 (50,7%) 235 (47,2%)

171 (56,1%)

326 (52,5%)

132 (47,7%)

38 / 79 (48,1%) 912 / 1882 (48,5%)

268 / 31 /

Other federal states Missing value Foreign countries Vienna Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Nationality - "high and low prevalence countries" High prevalence countries Low prevalence countries Nationality Austria Missing value High prevalence countries

174 / 111 /

96 /

171 /

63 /

138 / 252 (54,8%) 889 / 1552 (57,3%)

0,7 1

0,4

Styria Tyrol

Salzburg

Upper Austria

Carinthia

Other Heterosexual Federal state

0,6 556 (41,9%)

233 /

0,9 1

1388 / 2823 (49,2%) 476 / 931 (51,1%) 604 / 1394 (43,3%)

0,6

801 / 1877 (42,7%) 1063 / 1877 (56,6%)

Mode of transmission MSM IDU

<0,001 <0,001

<0,001

0,062 0,523

0,356 0,589 0,394 0,278 <0,001 0,187 0,069 0,133

0,2 –0,4

0,3 1

0,8 – 1,2 1,4 – 2,1

1,5 – 2,1

1,2 – 1,6 1,0 – 1,5

0,7 – 1,7

1,1 – 1,6 0,5 – 1,3

1,1 – 1,7 0,9 – 1,6

1,4 – 2,7

1,1 – 1,8

0,9 – 1,8

0,5 – 0,9

0,3 – 0,5

0,5 – 0,6

0,8 – 1,0

0,5 – 0,6

0,957 <0,001

<0,001

<0,001 0,014

0,707

0,005 0,338

0,007 0,139

<0,001

0,004

0,233

0,015

<0,001

0,118

<0,001

<0,001 0,047

<0,001 <0,001 0,002

<0,001

1,3 –1,9

1,6 1

0,5 –0,9

0,7 1

1,1 –1,5 0,9 –1,4

0,4 –0,7

1,3 1,1 1

0,5 –0,7 0,5

0,5 –0,7

0,6

<0,001

0,002 0,336

0,013

<0,001

Model 1 (N = 3754) Multivariable regression* OR (95% CI) p-value

1,2 –1,7 1,0 –1,7

1,8 –3,0 1,4 –2,5 0,2 –0,7

1,4 –2,0

1,4 1,3 1

2,3 1,9 0,3 1

1,7 1

Univariable regression OR (95% CI) p-value

1,4 – 2,5 0,2 – 0,6

≥ 39 years Gender Male Female

Frequencies N= 1864 / 3754 (49,7%)

/ 2526 (19,8%) / 30 (0,0%) / 587 (4,4%) / 611 (11,6%)

0,1 – 0,3

1,0 – 1,5 0,8 – 1,4

– 1,3 – 1,5 – 1,8 – 1,2 – 3,2 – 1,5 – 1,1 – 1,2

< 39 years

Age

0,2 1

/ 53 (5,7%) / 1283 (17,5%) / 525 (16,2%) / 1893 (15,1%)

3 225 85 285

0,5 0,8 0,8 0,6 1,7 0,9 0,2 0,2

<0,001 <0,001 0,002

<0,001

6.2.3

Demographic characteristics

1,2 1,1 1

/ 132 / 326 / 171 / 343 / 235 / 515 / 71 / 79 / 1882

16 53 30 44 69 90 5 7 284

2,3 – 3,4 1,8 – 3,0 0,2 – 0,7

1,2 – 1,9

1,3 – 1,9

Model 1 (N = 3754) Multivariable regression* p-value OR (95% CI)

Variable

2,8 2,3 0,3 1

/ 1394 (23,3%) / 556 (20,1%) (3,6%) / 252 / 1552 (9,8%)

325 112 9 152 0,8 1,1 1,2 0,8 2,3 1,2 0,4 0,5 1

1,5 1

485 / 2823 (17,2%) 113 / 931 (12,1%)

(12,1%) (16,3%) (17,5%) (12,8%) (29,4%) (17,5%) (7,0%) (8,9%) (15,1%)

1,6 1

Univariable regression p-value OR (95% CI)

356 / 1877 (19,0%) 242 / 1877 (12,9%)

Frequencies N= 598 / 3754 (15,9%)

Risk factors for an „early“ diagnosis

All centres

* adjusted for the variable: gender

Variable Demographic characteristics Age < 39 years ≥ 39 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Federal state Carinthia Upper Austria Salzburg Styria Tyrol Other federal states Missing value Foreign countries Vienna Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Nationality - "high and low prevalence countries" High prevalence countries Low prevalence countries Nationality Austria Missing value High prevalence countries Low prevalence countries

All centres

6.2.2 Risk factors for a „late“ diagnosis

“Late” diagnosis is defined as: CD4 cell count below 350 at time of HIV diagnosis and/or AIDS within 3 months of HIV diagnosis

6.2.4

Risk factors for mortality

Date of censoring: last contact with the HIV centre (95 missing)

All centres Variable Demographic characteristics Age < 39 years ≥ 39 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Nationality High prevalence countries Low prevalence countries Stage of disease Advanced diagnosis Yes No

Frequencies N = 270 / 3659 (7,4%)

Univariable regression HR (95% CI) p-value

Model 1 (N = 3659) Multivariable regression* HR (95% CI) p-value

114 / 1832 156 / 1827

(6,2%) (8,5%)

0,9 1

0,7 –1,1

0,304

216 / 2755 54 / 904

(7,8%) (6,0%)

1,5 1

1,1 –2,0

0,010

1,6 1

1,1 –2,2

0,006

55 87 26 102

/ 1373 (4,0%) / 544 (16,0%) / 226 (11,5%) / 1516 (6,7%)

0,7 2,4 2,3 1

0,5 –1,0 1,8 –3,2 1,5 –3,5

0,035 <0,001 <0,001

0,6 2,2 1,9 1

0,4 –0,8 1,6 –3,1 1,2 –3,0

0,002 <0,001 0,003

6 75 30 159

/ 44 (13,6%) / 1245 (6,0%) / 506 (5,9%) / 1864 (8,5%)

0,7 0,7 1

0,5 –0,9 0,4 –1,0

0,008 0,031

(3,9%) (8,0%)

0,5 1

0,3 –0,8

0,003

0,5 1

0,3 –0,8

0,007

135 / 1066 (12,7%) 135 / 2593 (5,2%)

2,4 1

1,9 – 3,1

<0,001

2,4 1

1,9 – 3,1

<0,001

22 / 558 248 / 3101

* adjusted for the variables: age, population size of area of residence

Survival after the HIV diagnosis

Patients still at risk:

Early: 591 509 420 361 301 249 Interm.: 2002 1611 1410 1217 1042 851 Advanced:1066 847 734 643 543 454

Patients still at risk:

MSM: IDU: Hetero: Others:

1373 1106 544 442 1516 1270 226 149

926 387 1125 126

769 346 1000 103

631 301 865 88

495 255 732 72

CO-INFECTIONS

7. Co-infections

7.1.3

7.1

This analysis only includes new “recent” syphilis infections defined as follows: patients with a former syphilis result that was either negative or a status post treatment and who now presented with active syphilis (= new „recent“ syphilis infections).

Syphilis

Syphilis can persist for several years when it is not treated, and reinfection with syphilis is possible because there is no protective immunity.

7.1.1

Missing values and status post syphilis diagnoses

Included are all patients seen since 1.1.2001.

„Recent“ syphilis infections: incidence

MSM with incident syphilis 164 (100,0%) 51 (31,1%) 113 (68,9%) 30 (26,5%)

7.1.2

Active syphilis: prevalence

The following analysis includes all active cases of syphilis by year of diagnosis (= new syphilis diagnoses). Therefore, recent syphilis cases and infections of unknown duration are included.

N Patients not on ART Patients on ART ART interruptions Mean duration of ART in months (± SD)* 57,9 Patients on ART since 2.5 m 109 HIV RNA <50 copies/ml 93 Chronic hepatitis B 9 Chronic hepatitis C 4 Resistance Any (on ART) 61 Any transmitted 64 Mean CD4 nadir (± SD) 263,3 Mean age (± SD) 40,5 * including patients with interruption

(± 62,5) (66,5%) (85,3%) (5,5%) (2,4%) (85,9%) (39,0%) (± 188,0) (± 10,3)

MSM without syphilis 1238 (100,0%) 287 (23,2%) 951 (76,8%) 223 (23,4%)

Odds ratio

97 (± 74,8) 879 (71,0%) 809 (92,0%) 31 (2,5%) 16 (1,3%)

p<0,001 2,23 0,50 2,26 1,91

504 154 257,1 45,2

(53,0%) (12,4%) (± 192,1) (± 11,7)

1,50 0,67 1,18

5,41 10,39 p>0,05 p<0,001

± 95% C.I. 1,05 to 0,47 to 0,76 to

2,14 0,95 1,84

0,80 0,28 1,06 0,63

6,23 0,90 4,84 5,78

to to to to

2,74 to 10,69 6,25 to 17,28

Incident cases of syphilis among HIV-infected MSM

7.2

Tuberculosis (last contact since 1.1.2005)

Tuberculosis is incompletely recorded in the HIV Patient Management System.

7.4

Hepatitis B (last contact since 1.1.2005)

Chronic HBV was defined by a positive result on a hepatitis B surface antigen (HBsAg) test or by a positive HBV DNA test result.

7.3

Hepatitis C (last contact since 1.1.2005)

HCV co-infection was defined by a positive result on a qualitative or quantitative RNA test. We assumed that patients with a positive HCV antibody test but without an available HCV RNA test were also co-infected with HCV. However, patients with a positive HCV antibody test and a negative result on an HCV RNA test were classified as HCV-negative.

Therapy for hepatitis B (patients currently in care; data from July 2012)

Current guidelines recommend the use of tenofovir and emtricitabine or tenofovir and lamivudine as the NRTI-backbones in cART combinations for HBV-HIV co-infected patients. Most of the HBV-HIV co-infected patients (93.2%) in care at one of the Austrian HIV treatment centres received an NRTI-backbone to help control the HBV infection.

Chronic hepatitis B (last contact since 1.1.2005)

Age (years ± SD) Federal state Upper Austria Styria Tyrol Others/missing value/foreign countries Vienna Gender Male Female Mode of transmission MSM IDU Others/missing value Hetero Coinfection with HBV/HCV AIDS CD4 nadir (cells/µl ± SD) Current CD4 (cells/µl ± SD) Stage of disease Liver cirrhosis Current renal insufficiency (stage 3, 4, 5) Last bilirubin (mg/dl ± SD) Last PT (% ± SD) Last patelet count (G/l ± SD) Hepatitis therapy Currently on therapy Previous treatment Follow-up Death Alive, no follow-up in the last 12 months Follow-up in the last 12 months and on ART Follow-up in the last 12 months and not on ART Last HIV RNA (living participants)* <400 copies/ml ≤50 copies/ml

Chronic hepatitis B N = 181 41,6 ± 10,7 14 11 16 18 122

7,7% 6,1% 8,8% 9,9% 67,4%

143 38

79,0% 21,0%

56 30,9% 48 26,5% 11 6,1% 66 36,5% 23 12,7% 74 40,9% 176 ± 164 421 ± 298 20 11,0% 17 9,4% 1,4 ± 3,0 88 ± 23,3 200 ± 80,5 125 -

69,1%

41 29 106 5

22,7% 16,0% 58,6% 2,8%

95 82

52,5% 45,3%

* Patients without measurement since ≥ 12 months were counted as virological failure

TRANSMISSION OF DRUG RESISTANT HIV

8.2

8. Transmission of drug resistant HIV The rate of transmission of drug resistant HIV („percent with resistance“) corresponds to the number of patients with resistance mutations in relation to the number of patients with a genotypic resistance test before antiretroviral therapy. For this, the genomes of the reverse transcriptase (RT) and the protease (P) were sequenced. The resistance mutations have been classified according to Bennett DE et al. Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update. PLoS One 2009;4(3):e4724. Patients were either analysed according to the time of the infection („recent infection“), or, if this was not known, patients were analysed according to the year of the HIV diagnosis.

NRTI M41 K65 D67 T69 K70 L74 V75 F77 Y115 F116 Q151 M184 L210 T215 K219

NNRTI

L R N, G, E D, ins R, E V, I T, M, A, S L F Y M V, I W Y, F, I, S, C, D, V, E Q, E, N, R

L100 K101 K103 V106 V179 Y181 Y188 G190 P225 M230

Number of "recent" HIV infections

I E, P N, S M, A F C, I, V L, H, C A, S, E H L

L23 L24 D30 V32 M46 I47 G48 I50 F53 I54 G73 L76 V82 N83 I84 I85 N88 L90

I I N I I, L V, A V, M V, L L, Y V, L, M, A, T, S S, T, C, A V A, T, F, S, C, M, L D V, A, C V D, S M

Year of HIV diagnosis 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Total

Available resistance tests before ART

Any resistance

All centers

CASCADE centers

All centers

CASCADE centers

All centers

CASCADE centers

286 306 293 331 328 324 336 352 298 313 301 286

191 214 200 213 228 238 250 265 229 229 224 217

118 130 162 210 193 206 209 220 210 237 216 188

49 67 96 127 128 150 155 184 168 182 165 155

4 11 10 12 11 15 14 16 23 22 19 9

2 7 6 7 8 14 11 13 20 16 13 8

3754

2698

2299

1626

166

125

Available resistance tests before ART

Any resistance

All centers

CASCADE centers

All centers

CASCADE centers

All centers

CASCADE centers

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

59 36 51 59 60 44 63 57 52 75 60 23

29 19 24 41 41 35 48 47 43 59 46 17

41 22 38 43 39 32 44 41 44 54 46 14

15 8 16 28 28 27 37 34 37 46 37 10

3 4 3 3 8 4 6 6 3 1

1 2 2 3 7 3 5 5 1 1

MSM IDU Other Heterosexual

342 121 10 166

282 57 3 107

257 73 6 122

215 32 2 74

27 5 9

22 1 7

639

449

458

323

Year of "recent" HIV infection

Mode of transmission

Number of patients with resistance test before HIV therapy Number of HIV diagnoses

Calculation of the time of infection (year of the HIV infection): • Time point of the acute HIV infection or • Midpoint between last negative and first positive HIV test

Protease

„Recent“ infection means: • Acute HIV infection (westernblot pattern or antigen/HIV RNA with clinical symptoms) • Documented seroconversion with a negative HIV test not more than 3 years before the first positive test

The following codons and amino acids were classified as resistance:

Reverse Transkriptase

8.1

„Recent” infection (time of infection known or estimated)

Total

Overall rate of transmitted drug resistance in recent infection was 9.3% (30 of 323). No risk factors for transmitted resistance in “recent” infections were identified.

224 225 449

Total

381 68

330

160 170

287 43

220 32 2 76

153 73 104 -

199 86 163 1 282 57 3 107

15 8 17 28 28 28 39 36 37 46 37 11

29 19 24 41 41 35 48 47 43 59 46 17

323

158 165

281 42

215 32 2 74

150 71 102 -

15 8 16 28 28 27 37 34 37 46 37 10

Attempted Number of resistance Available tests resistance HIV tests infections before ART

< 32 years e 32 years

Age at time of HIV-test

Male Female

Gender

MSM IDU Others/missing value Hetero

Mode of transmission

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Population size of area of residence < 100 000 ≥ 100 000 > 1 million Missing value

Year of HIV infection

"Recent" infections

293

141 152

252 41

193 31 2 67

138 62 93 -

14 8 14 26 25 27 30 31 32 41 36 9

Wild type

17 13

29 1

22 1 7

12 9 9 -

1 2 2 3 7 3 5 5 1 1

Any resistance NNRTI 1 2 2 2 3 3 1 -

5 5 4 12 2 14 6 8 14

NRTI 1 1 1 5 1 1 1 1

4 3 5 8 1 3 11 1 8 4 12

4 7

11 -

8 3

8 1 2 -

1 3 2 3 1 1 -

1 2

3 -

2 1

2 1 -

1 1 1 -

Resistance to NRTI and PI PI

2 -

1 1 -

2 -

NRTI and NNRTI

3 -

1 -

1 0

1 1 1 -

3 -

3-classresistance

NNRTI and PI

Transmission of drug resistant HIV according to the time of the "recent" HIV infection, residence, mode of transmission, gender and age

8.3

Total

Unknown time of infection (not “recent”)

Patients from high prevalence areas had a lower risk of transmitted resistance (OR=0.44, 95% CI: 0.200.99).

Number of HIV diagnoses

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

MSM IDU Other Heterosexual

Available resistance tests before ART Any resistance

Year of HIV diagnosis

Mode of transmission

All centers CASCADE centers All centers CASCADE centers All centers CASCADE centers

240 258 251 265 271 276 285 287 245 248 230 237 166 191 177 179 189 201 213 212 186 180 166 178 90 99 132 161 158 170 173 171 172 183 164 155 37 57 83 104 104 121 126 142 137 139 121 127 2 10 8 10 8 12 12 9 17 18 11 8 1 7 4 7 6 11 9 8 15 13 7 7

1049 426 242 1376 838 245 143 1012 669 227 111 821 530 106 69 593 60 9 8 48 49 4 7 35

3093 2238 1828 1298 125 95

1119 1119 2238

Total

1632 606

1339

615 724

984 355

535 113 73 618

571 278 479 11

851 431 926 30 838 245 143 1012

37 59 89 105 113 124 133 143 140 145 123 128

166 191 177 179 189 201 213 212 186 180 166 178

1298

592 706

961 337

530 106 69 593

553 266 468 11

37 57 83 104 104 121 126 142 137 139 121 127

Attempted Number of resistance Available HIV tests resistance diagnoses before ART tests

< 34 years e 34 years

Age at time of HIV-test

Male Female

Gender

MSM IDU Others/missing value Hetero

Mode of transmission

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Population size of area of residence < 100 000 â&#x2030;Ľ 100 000 > 1 million Missing value

Year of HIV diagnosis

Not-"recent" infections

1203

544 659

884 319

481 102 62 558

507 247 439 10

36 50 79 97 98 110 117 134 122 126 114 120

Wild type

48 47

77 18

49 4 7 35

46 19 29 1

1 7 4 7 6 11 9 8 15 13 7 7

Any resistance

22 23

34 11

22 1 4 18

23 5 16 1

1 5 2 2 4 6 5 4 5 5 2 4

NRTI

14 7

19 2

13 1 1 6

7 11 3 -

1 1 2 1 1 1 2 2 6 2 2

NNRTI

14 18

26 6

16 2 2 12

16 3 13 -

1 1 3 2 4 3 2 8 4 3 1

2 1

3 -

1 2 0

Resistance to NRTI and PI PI

0 0

NRTI and NNRTI

0 0

NNRTI and PI

Transmission of drug resistant HIV according to the time of the HIV diagnosis, residence, mode of transmission, gender and age

0 0

3-classresistance

ANTIRETROVIRAL THERAPY (ART)

9. Antiretroviral therapy (ART) 9.1

Therapy regimens on January 1, 2013

Patients currently in care regarding treatment status

Therapy regimens in the patients currently in care

9.2

Regimens of antiretroviral therapy

39 patients have currently PI (Mono). Use of therapy regimens over time

9.3

Administered antiretroviral drugs

9.3.1

Use of NRTI

NRTI

9.3.5

Integrase inhibitor

Number of patients treated with the drug 01.01.02 01.01.06 01.01.08 01.01.10 01.01.11 01.01.12 01.07.12 01.01.13

Abacavir

277

488

702

631

743

756

782

804

Didanosin

310

117

174

577

1061

1760

2069

2267

2361

Emtricitabin Lamivudin

931

1312

1341

871

1098

1014

1021

1010

Stavudin

567

119

Tenofovir

782

1058

1255

1973

2215

2396

2454

Zidovudin

385

431

294

163

114

102

9.3.2 NNRTI

Number of patients treated with the drug 01.01.02 01.01.06 01.01.08 01.01.10 01.01.11 01.01.12 288

437

Etravirin Nevirapin

357

312

01.07.12 01.01.13

500

616

782

809

768

742

295

270

416

458

484

487

148

255

Rilpivirin

9.3.3

01.01.02 01.01.06 01.01.08 01.01.10 01.01.11 01.01.12 01.07.12 01.01.13

Raltegravir

9.3.6

208

313

Darunavir 400 mg Darunavir 600 mg Fosamprenavir

339

505

514

556

559

134

382

587

670

696

106

104

100

163

154

101

153

148

142

121

Lopinavir/r

202

350

650

441

473

336

276

239

Saquinavir

Tipranavir

134

412

562

611

1096

1306

1429

1427

Ritonavir as booster

Enfuvirtide

286

337

233

130

"Epivir"

605

738

512

233

282

229

207

177

172

557

564

664

682

720

743

"Retrovir" "Kivexa"

143

569

740

1273

1473

1556

1555

"Trizivir"

"Ziagen"

237

251

106

318

476

572

555

546

136

232

"Atripla" "Eviplera"

9.3.7

Use of NRTI combinations

Mostly, a combination of 2 NRTI is used; however, at least 19 patients receive â&#x2030;Ľ3 NRTI. Number of patients treated with the drug

Maraviroc

172

571

1060

1751

2052

2251

2342

Abacavir + Lamivudin

Tenofovir + Emtricitabin

289

409

663

613

715

729

759

783

Tenofovir + Lamivudin

321

511

431

165

187

126

110

Zidovudin + Lamivudin

407

273

154

106

Abacavir + Zidovudin

Tenofovir + Abacavir

Tenofovir only

Abacavir only

Lamivudin only

Proportion of patients who have received NRTI-, NNRTI- and PI-drugs Patients currently in care (N= 3880)

01.01.02 01.01.06 01.01.08 01.01.10 01.01.11 01.01.12 01.07.12 01.01.13 18

NRTI-, NNRTI- and PI-drugs ever received Percentage with current HIV RNA â&#x2030;Ľ 400 copies/ml

494

01.01.02 01.01.06 01.01.08 01.01.10 01.01.11 01.01.12 01.07.12 01.01.13

Number of patients treated with the drug

500

"Combivir"

9.3.8

Use of entry-/ fusion inhibitors

Entry-/ fusion inhibitors

482

01.01.04 01.01.06 01.01.08 01.01.10 01.01.11 01.01.12 01.07.12 01.01.13

01.01.02 01.01.06 01.01.08 01.01.10 01.01.11 01.01.12 01.07.12 01.01.13 0

362

Number of patients treated with the drug

Atazanavir

128

Use of commercial preparations

NRTI

Use of PI

9.3.4

Number of patients treated with the drug

"Truvada"

Use of NNRTI

Efavirenz

Use of integrase inhibitors

1419 (36,6%) 81 (5,7%)

Patients currently in care and on ART (N = 3597) 1410 (39,2%) 74

(5,2%)

9.4

CD4 cell counts at initiation of ART

9.4.2

9.4.1

CD4 cell counts at initiation of ART

TOTAL

Median CD4 count at ART initiation

Transmission risk

CD4 count categories and time elapsed between HIV diagnosis and initiation of ART

Initial therapy Patients initiating ART <200 and < 6 months <200 and > 6 months 200-350 and < 6 months 200-350 and > 6 months >350 No CD4 count before ART Median CD4 count at ART initiation 82

Level of education (Graz and OWS excluded)

Status of employment (Graz and OWS excluded)

2003 2005 2007 2009 2010 2011 2012 (%) N (%) N (%) N (%) N (%) N (%) N (%) N 213 260 326 362 385 400 411 60 (28,2) 62 (23,8) 65 (19,9) 70 (19,3) 68 (17,7) 59 (14,8) 73 (17,8) 38 (17,8) 49 (18,8) 67 (20,6) 47 (13,0) 41 (10,6) 36 (9,0) 38 (9,2) 21 (9,9) 29 (11,2) 35 (10,7) 41 (11,3) 41 (10,6) 52 (13,0) 53 (12,9) 27 (12,7) 62 (23,8) 80 (24,5) 84 (23,2) 87 (22,6) 58 (14,5) 43 (10,5) 37 (17,4) 37 (14,2) 50 (15,3) 82 (22,7) 119 (30,9) 165 (41,3) 170 (41,4) 30 (14,1) 21 (8,1) 29 (8,9) 38 (10,5) 29 (7,5) 30 (7,5) 34 (8,3) 192

208

228

258

284

334

317

9.5

Initial therapy

9.5.1

Number of persons who started ART in the respective year

9.5.3

Antiretroviral drugs in the initial therapy

NRTI

Number of patients treated with the drug 1. ART 09/2 1. ART 10/1 1. ART 10/2 1. ART 11/1 1. ART 11/2 1. ART 12/1 1. ART 12/2

Abacavir Didanosin Emtricitabin

9.5.2

(N = 194)

(N = 193)

(N = 195)

(N = 207)

(N = 194)

115

150

170

178

155

175

150

Tenofovir

116

152

171

178

156

176

149

Zidovudin

Regimens of the initial therapy

After July 1st, 2012, 194 patients started antiretroviral therapy. 110 of them also had their first measurement of CD4 cell count within this period.

(N = 174)

Stavudin

Lamivudin

(N = 143)

Initial therapy

NNRTI

Number of patients treated with the drug 1. ART 09/2 1. ART 10/1 1. ART 10/2 1. ART 11/1 1. ART 11/2 1. ART 12/1 1. ART 12/2

Efavirenz

(N = 143)

(N = 174)

(N = 194)

(N = 193)

(N = 195)

(N = 207)

(N = 194)

Etravirin Nevirapin

Rilpivirin

Number of patients treated with the drug 1. ART 09/2 1. ART 10/1 1. ART 10/2 1. ART 11/1 1. ART 11/2 1. ART 12/1 1. ART 12/2

(N = 143)

(N = 174)

(N = 194)

(N = 193)

(N = 195)

(N = 207)

(N = 194)

Atazanavir

Darunavir 400

Fosamprenavir

Lopinavir/r

Ritonavir as booster

102

113

Number of patients treated with the drug Entry/ fusion inhibitor 1. ART 09/2 1. ART 10/1 1. ART 10/2 1. ART 11/1 1. ART 11/2 1. ART 12/1 1. ART 12/2 Maraviroc

Integrase inhibitor Raltegravir

(N = 143)

(N = 174)

(N = 194)

(N = 193)

(N = 195)

(N = 207)

(N = 194)

Number of patients treated with the drug 1. ART 09/2 1. ART 10/1 1. ART 10/2 1. ART 11/1 1. ART 11/2 1. ART 12/1 1. ART 12/2 (N = 143)

(N = 174)

(N = 194)

(N = 193)

(N = 195)

(N = 207)

(N = 194)

9.6.2

Number of patients treated with the drug 1. ART 09/2 1. ART 10/1 1. ART 10/2 1. ART 11/1 1. ART 11/2 1. ART 12/1 1. ART 12/2 (N = 143)

(N = 174)

(N = 194)

(N = 193)

(N = 195)

(N = 207)

(N = 194)

"Combivir"

"Epivir"

"Retrovir"

"Kivexa"

"Truvada"

120

130

135

117

123

100

"Trizivir"

"Ziagen"

"Atripla"

"Eviplera"

9.6

ART switches and interruptions

9.6.1

Switches and interruptions of ART during the first year of treatment

ART switches and interruptions per calendar year

The calculations include all patients who were seen since January 1st, 2005. Percentage of patients with ART switches and interruptions

2004 2005 2006 2007 2008 2009 2010 2011 2012

% of patients with ART switches 28,4% 29,4% 26,2% 22,5% 22,9% 19,5% 19,7% 16,5% 17,7%

% of patients with >1 ART switch 7,1% 5,9% 4,5% 4,0% 4,1% 3,7% 3,5% 3,1% 3,0%

% of patients with ART interruptions 8,0% 10,4% 6,7% 6,1% 5,3% 4,9% 3,9% 3,9% 2,4%

% of patients with >1 ART interruption 0,4% 0,8% 0,6% 0,5% 0,4% 0,4% 0,4% 0,3% 0,2%

Percentage of patients with ART switches and interruptions during the first year of treatment

Year of ART initiation 2004 2005 2006 2007 2008 2009 2010 2011

% of patients with ART switches 39,1% 37,3% 22,5% 25,5% 24,2% 27,9% 21,3% 23,4%

% of patients with >1 ART switch 11,2% 13,8% 4,5% 5,8% 7,4% 7,7% 5,5% 5,8%

% of patients with ART interruptions 21,0% 18,1% 11,6% 13,8% 11,7% 10,2% 7,5% 6,1%

% of patients with >1 ART interruption 1,3% 0,8% 0,7% 1,2% 0,9% 0,3% 0,3% 1,0%

Patients seen since 1.1.2005: long-term frequency of treatment switches and interruptions (ART initiation between 1.1.2002 and 1.1.2005) Percentage of persons with treatment switches since 2004 (504 / 589) Percentage of persons with treatment interruptions since 2004 (167 / 589)

% 85,6 28,4

9.6.3

Risk factors for treatment interruptions since 2007

9.6.4

The calculations include all living patients who were seen since January 1st, 2005 and who have initiated ART before 2008. All centres Variable Demographic characteristics Age <48 years ≥48 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Federal state Carinthia Upper Austria Salzburg Styria Tyrol Other federal states Missing value Foreign countries Vienna Population size of area of residence Missing < 100 000 ≥ 100 000 > 1 million Nationality High prevalence countries Low prevalence countries Stage of disease AIDS Yes No CD4 nadir Missing <200 cells/µl 200-349 cells/µl ≥350 cells/µl

Frequencies N= 420 / 2662 (15,8%)

Model 1 (N = 2662) Univariable regression Multivariable regression* OR (95% CI) p-value OR (95% CI) p-value

272 / 1333 148 / 1329

(20,4%) (11,1%)

2,0 1

1,6 –2,5

<0,001

268 / 1862 152 / 800

(14,4%) (19,0%)

0,7 1

0,6 –0,9

0,003

98 126 24 172

/ / / /

897 423 180 1162

(10,9%) (29,8%) (13,3%) (14,8%)

0,7 2,4 0,9 1

0,5 –0,9 1,9 –3,2 0,6 –1,4

0,010 <0,001 0,604

12 46 27 20 51 48 2 3 211

/ / / / / / / / /

83 304 125 209 263 371 5 50 1252

(14,5%) (15,1%) (21,6%) (9,6%) (19,4%) (12,9%) (40,0%) (6,0%) (16,9%)

0,8 0,9 1,4 0,5 1,2 0,7 1

0,4 0,6 0,9 0,3 0,8 0,5

–1,6 –1,2 –2,1 –0,8 –1,7 –1,0 -

0,572 0,469 0,182 0,008 0,323 0,071 -

2 122 85 211

/ 4 / 980 / 426 / 1252

(50,0%) (12,4%) (20,0%) (16,9%)

0,7 1,2 1

0,6 – 0,9 0,9 – 1,6

0,004 0,148

54 / 266 366 / 2396

(20,3%) (15,3%)

1,4 1

1,0 –1,9

0,034

168 / 982 252 / 1680

(17,1%) (15,0%)

1,2 1

0,9 –1,4

0,150

0 290 102 28

(0,0%) (17,7%) (13,1%) (11,4%)

1,7 1,2 1

1,1 –2,5 0,8 –1,8

0,015 0,483

/ 7 / 1634 / 776 / 245

* adjusted for the variables: gender, nationality, AIDS, duration of treatment

2,0 1

0,8 2,5 0,9 1

0,7 1,3 1

1,6 –2,5

0,6 –1,1 1,9 –3,3 0,6 –1,5

0,6 –0,9 0,9 –1,7

<0,001

0,145 <0,001 0,680

0,011 0,112

Risk factors for treatment switches since 2007

The calculations include all living patients who were seen since January 1st, 2005 and who have initiated ART before 2008. All centers Frequencies N= Variable 1909 / 2662 (71,7%) Demographic characteristics Age <48 years 920 / 1333 (69,0%) 989 / 1329 (74,4%) ≥48 years Gender Male 1328 / 1862 (71,3%) Female 581 / 800 (72,6%) Mode of transmission MSM 624 / 897 (69,6%) IDU 331 / 423 (78,3%) Other 130 / 180 (72,2%) Heterosexual 824 / 1162 (70,9%) Federal state Carinthia 55 / 83 (66,3%) Upper Austria 237 / 304 (78,0%) Salzburg 101 / 125 (80,8%) Styria 159 / 209 (76,1%) Tyrol 214 / 263 (81,4%) Other federal states 263 / 371 (70,9%) Missing 2 / 5 (40,0%) Foreign countries 20 / 50 (40,0%) Vienna 858 / 1252 (68,5%) Population size of area of residence Missing 2 / 4 (50,0%) < 100 000 714 / 980 (72,9%) ≥ 100 000 335 / 426 (78,6%) > 1 million 858 / 1252 (68,5%) Nationality High prevalence areas 180 / 266 (67,7%) Low prevalence countries 1729 / 2396 (72,2%) Stadium of disease AIDS Yes 748 / 982 (76,2%) No 1161 / 1680 (69,1%) CD4 Nadir Missing 0 / 7 (0,0%) <200 cells/µl 1216 / 1634 (74,4%) 200-349 cells/µl 541 / 776 (69,7%) ≥350 cells/µl 152 / 245 (62,0%)

Model 1 (N = 2662) Univariable Regression Multivariable Regression* OR (95% CI) p-value OR (95% CI) p-value

0,8 1

0,6 –0,9

0,002

0,9 1

0,8 –1,1

0,494

0,9 1,5 1,1 1

0,8 –1,1 1,1 –1,9 0,8 –1,5

0,507 0,004 0,718

0,9 1,6 1,9 1,5 2,0 1,1 1

0,6 1,2 1,2 1,0 1,4 0,9

–1,4 –2,2 –3,1 –2,1 –2,8 –1,4 -

0,667 0,001 0,005 0,029 <0,001 0,388 -

1,2 1,7 1

1,0 –1,5 1,3 –2,2

0,026 <0,001

0,8 1

0,6 –1,1

0,123

1,4 1

1,2 –1,7

<0,001

1,8 1,4 1

1,3 –2,4 1,0 –1,9

<0,001 0,025

0,8 1

0,7 –1,0

0,042

1,0 1,5 1,1 1

0,8 –1,2 1,1 –1,9 0,8 –1,6

0,729 0,006 0,639

1,2 1,6 1

1,0 –1,5 1,3 –2,1

0,040 <0,001

1,3 1

1,1 –1,6

0,002

* adjusted for the variables: gender, nationality, duration of treatment

9.7

Drug discontinuation within 2 years of starting a drug (since 2007)

Atazanavir: INITIAL NOT INITIAL

Abacavir: INITIAL NOT INITIAL

Darunavir 400mg: INITIAL

NOT INITIAL

Tenofovir: INITIAL NOT INITIAL

Fosamprenavir: INITIAL NOT INITIAL

Efavirenz: INITIAL NOT INITIAL

Lopinavir/r INITIAL NOT INITIAL

Nevirapin: INITIAL NOT INITIAL

Raltegravir INITIAL NOT INITIAL

92 93

0,4 0,4 0,4 16,9 21,4 10,1 1,6 0,8 8,5 3,6 100%

1,6

15,9 11,1 15,9 4,8 3,2 4,8 3,2 100%

0,8

0,8 3,2 0,4 2,0

2,4 1,2 0,8 0,4 2,8 17,3 0,8

3,2

1,6

3,2

1,6

11,1 1,6 6,3

4,8 1,6

0,8 0,4 0,4

1,2

1,6 1,6

Tenofovir

1,6

Abacavir

9,7 4,0 8,9 1,6 3,2 3,2 0,8 100%

2,4 0,8

0,8

3,2

41,1 0,8

0,8

7,3

0,8 0,8 0,8

4,0

Efavirenz

3,1 6,3 9,4 100%

3,1 6,3 9,4

3,1

6,3

3,1

28,1

15,6 3,1

3,1

Nevirapin

Treatment failure (i.e. virological, immunological, and/or clinical failure) Virological failure Partial virological failure Immunological failure - CD4 drop Clinical progression Abnormal fat redistribution Concern of cardiovascular disease Dyslipidaemia Cardiovascular disease Hypersensitivity reaction Toxicity, predominantly from abdomen/ GI tract Toxicity - GI tract Toxicity - Liver Toxicity - Pancreas Toxicity, predominantly from nervous system Toxicity, predominantly from kidneys Toxicity, predominantly from endocrine system Diabetes Haematological toxicity (anemiaâ&#x20AC;Ś etc.) Hyperlactataemie/lactic acidosis Death Side effects - any of the above but unspecified Comorbidity Toxicity, not mentioned above Availability of more effective treatment (not specifically failure or side effect related) Simplified treatment available Treatment too complex Drug interaction Structured Treatment Interruption (STI) Structured Treatment Interruption (STI) - at high CD4 Patient's wish/ decision, not specified above Non-compliance Physician's decision, not specified above Pregnancy Study treatment Other causes, not specified Unknown Total

NOT-INITIAL THERAPY

2,3 11,4 9,1 100%

11,4 15,9 6,8

23,4 6,4 12,8 2,1 2,1 8,5 4,3 100%

3,0 3,0 100%

18,2 6,1 9,1 12,1

3,0 2,1

6,8

6,1

27,3

3,0

3,0 3,0

Efavirenz

3,0

4,3

4,3 4,3 2,1

8,5 10,6

4,3

Tenofovir

4,5

2,3 6,8

4,5 2,3

4,5

9,1

2,3

Abacavir

6,4 6,4 100%

8,5 4,3 10,6

4,3

8,5

2,1

4,3

8,5 4,3 2,1 12,8

14,9

2,1

Nevirapin

8,3 1,7 100%

18,3 10,0 10,0 1,7

1,7

6,7

1,7

1,7 5,0 5,0 15,0 1,7 1,7

1,7

1,7 5,0

Atazanavir

17,0 11,0 13,0 1,0 2,0 4,0 1,0 100%

2,0

9,0

2,0

3,0

1,0

2,0

6,0 7,0 13,0

1,0

3,0 1,0

1,0

Atazanavir

Reasons for discontinuation of drugs in not-initial therapy (since 2007, in %)

INITIAL THERAPY

Reasons for discontinuation of drugs in the initial therapy (since 2007, in %)

21,0 13,6 12,5 1,7 0,6 6,3 1,7 100%

7,4 0,6 2,3

0,6

2,8

1,1

1,1 0,6 1,1

4,5 6,8 1,1

1,7 1,7 1,1 1,1

2,8 4,0

Darunavir 400 mg

100%

19,8 11,1 9,9 2,4 3,7 11,1

1,2

18,5

1,2

2,5 2,5 11,1

1,2

1,2 1,2

1,2

Darunavir 400 mg

4,7 3,9 100%

11,2 12,9 9,9 1,7

10,7 0,4 1,3 0,4

0,4

0,9 3,4

0,4

10,3 17,2 0,9 0,9 0,9

0,9 2,1 3,0

0,4 0,4 0,4

8,1 2,7 100%

16,2 8,1 29,7

13,5

2,7 2,7 2,7

2,7 2,7

2,7

100%

12,5

12,5 29,2 8,3

4,2

8,3 8,3

4,2

8,3

4,2 100%

8,3 12,5 8,3

16,7

12,5 20,8

4,2

12,5

100%

22,0 9,8 9,8 4,8 2,4 12,2

12,2

2,4

4,9

9,8

2,4

Fosamprenavir Lopinavir/r Raltegravir

5,9 5,9 2,9 100%

11,8 20,6 8,8

5,9

2,9 2,9 2,9

14,7

2,9

2,9 5,9

2,9

Fosamprenavir Lopinavir/r Raltegravir

9.8

Frequency of drug dosing (data from July 2012)

9.9

9.8.1 Overview

Access to antiretroviral therapy

Summary table of indicators of access to HIV-related health care

123 of 3839 (3.2%) patients do not take any drugs at all and 202 (5.3%) patients have no ART but take other drugs. 699 (18.2%) patients are receiving ART only.

Number of patients

All centres

Total

Antiretrovirals (ARVs) (Fig.1)

325

2496

988

3839

Drugs other than ARVs (Fig. 2)

822

1070

835

648

464

3839

Overall dosing frequency (Fig. 3)

123

1093

1262

832

529

3839

993

715

491

297

2496

Dosing frequency

Overall dosing frequency in patients with once daily ARVs (Fig. 4) Fig. 1

Fig. 2

Fig. 3

Fig. 4

9.8.2

Frequency of virologic failure related to dosing frequency N

Dosing frequency Dosing frequency of ARVs Overall dosing frequency in patients with ARVs

HIV-RNA e400 1

HIV-RNA e400

2496 65 (2,6%) 988 48 (4,9%)

HIV-RNA e400 3

2 (6,7%)

HIV-RNA e400

HIV-RNA e400 Total

3514 115 (3,3%)

993 13 (1,3%) 1214 34 (2,8%) 802 34 (4,2%) 505 34 (6,7%) 3514 115 (3,3%)

Overall dosing frequency in 993 13 (1,3%) 715 12 (1,7%) 491 18 (3,7%) 297 22 (7,4%) 2496 patients with once daily ARVs

Variable Demographic characteristics Age <44/45/45 years ≥44/45/45 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence < 100 000 ≥ 100 000 > 1 million Nationality High prevalence countries Low prevalence countries Stage of disease CD4 nadir < 200 cells/µl 200-349 cells/µl ≥350 cells/µl ART ART use ever Yes No

Risk factors for no follow-up in the last 12 months

Risk factors for not receiving ART despite a CD4 nadir <350 and/or AIDS

Risk factors for starting ART with a CD4 <200 more than 6 months after the HIV diagnosis

OR (95% CI)*

OR (95% CI)**

OR (95% CI)***

0,7 1

(0,6 –0,9)

1,3 1

(1,1 –1,6)

1,1 1,3 2,3 1

(0,9 –1,4) (1,1 –1,6) (1,8 –3,0)

1,3 1,7 3,0 1

(0,9 –1,8) (1,2 –2,5) (2,0 –4,4)

0,6 (0,4 – 0,8) 1,8 (1,3 – 2,4) 1,1 (0,7 – 1,9) 1

0,4 0,3 1

(0,4 –0,5) (0,3 –0,4)

0,5 0,6 1

(0,4 –0,7) (0,4 –0,8)

0,7 (0,5 – 0,9) 0,6 (0,4 – 0,9) 1

2,8 1

(2,2 –3,5)

2,3 (1,6 –3,2) 1 Not applicable

0,1 1

Not applicable

(0,1 –0,1)

* adjusted for the variables: CD4 nadir ** adjusted for the variables: age, gender *** adjusted for the variables: age, gender, nationality

65 (2,6%)

(HIV-RNA ≥ 400: persons with at least 2.5 months between ART beginning and measurement of viral load) 94

BENEFITS OF ANTIRETROVIRAL THERAPY

C Death rate (all-cause mortality) of patients with AIDS * adjusted for the variables: gender

Variable Demographic characteristics Age <45 years e45 years Gender Male Female Mode of transmission MSM IDU Others/missing value Hetero HIV treatment centre Centre 1 Centre 2 Centre 3 Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Stage of disease CD4 nadir Missing value < 50 cells/µl 50-199 cells/µl e200 cells/µl Year of AIDS diagnosis 1991 - 1994 1995 - 1997 1998 - 2001 2002 - 2011

2,0 – 3,6 1,2 – 2,1

2,7 1,6 1

(55,0%) (50,9%) (43,4%)

(82,6%) (41,2%) (53,0%) (57,4%)

(92,9%) (60,6%) (42,2%) (27,7%)

533 / 969 193 / 379 157 / 362

/ 23 / 563 / 300 / 824

/ 42 / 914 / 559 / 195 / 507 / 316 / 322 / 565

19 232 159 473

39 554 236 54 448 177 139 119

(88,4%) (56,0%) (43,2%) (21,1%)

0,5 – 0,7 0,6 – 0,8

0,6 0,7 1

(53,0%) (66,2%) (61,4%) (33,8%)

511 488 176 535

5,5 2,2 1,6

1,7 1,3 1

1,8 2,2 2,8 1

4,5 – 6,7 1,7 – 2,7 1,2 – 2,0

3,1 – 4,7 1,7 – 2,7 1,4 – 2,3

3,8 2,2 1,8 1 <0,001 <0,001 <0,001

1,5 – 2,6 1,2 – 2,1

2,0 1,5 1

<0,001 0,002

0,6 – 0,8 0,6 – 0,9

1,0 – 1,6 1,1 – 1,7 1,3 – 2,1

2,2 – 3,0

0,7 0,7 1

<0,001 0,022

1,4 – 2,1 1,0 – 1,6

1,3 1,4 1,7 1

2,6 1

<0,001 <0,001 <0,001

<0,001 0,004

<0,001 0,002

0,041 <0,001 <0,001

<0,001

Model 1 (N = 1710) Multivariable regression* p-value HR (95% CI)

<0,001 <0,001

<0,001 <0,001 <0,001

0,002

<0,001

1,5 – 2,2 1,8 – 2,6 2,2 – 3,5

1,1 – 1,5

271 323 108 181

1,3 1

(53,1%) (47,3%)

2,7 – 3,6

678 / 1277 205 / 433

3,1 1 (68,1%) (35,2%) 582 / 855 301 / 855

/ / / /

A Univariable regression p-value HR (95% CI)

The documentation of death is partially incomplete in the HIV Patient Management System (e.g. considerable proportion of patients without follow-up since 2001 are not documented dead but presumed dead, see chapter 4.3). The graphs below show survival in patients with AIDS. In figure A, the patients of three HIV treatment centres were censored on January 1, 2013. Figure C shows death rates of these patients for different years.

Frequencies N= (51,6%) 883 / 1710

10.1 Mortality of patients with AIDS since 1985

3 of 7 centres

Risk factors for mortality after the diagnosis AIDS

10. Benefits of antiretroviral therapy

10.2 Mortality in combination ART era (years 2005-2010)

Death rate in all HIV-infected patients

10.2.1 Causes of death

Death rates in different age groups

Causes of death (all patients)

Causes of death (men)

Death rates according to transmission risk

Causes of death (women)

10.2.2 Death rate

100

Death rates according to causes of death

101

10.3 CD4 cell counts

10.3.1.2 Most recent CD4 cell count by duration of therapy

10.3.1 CD4 cell counts: nadir and most recent

The analysis includes only patients who initiated cART after January 1, 1997.

10.3.1.1 Overview Median CD4 cell counts

CD4 nadir

Recent CD4 cell count

Below only patients without a treatment interruption (see blue curves in above mentioned chart) are shown due to their last CD4 count before ART.

Most recent CD4 cell count

102

103

10.3.2 Increase of CD4 cells during ART

10.3.2.1 Factors associated with a recent CD4 cell count >500/µl All centres

The analysis includes only patients who initiated cART after January 1, 1997.

Below only patients without a treatment interruption (see blue curves in above mentioned chart) are shown below due to their last CD4 count before ART.

Variable Demographic characteristics Age <44 years ≥44 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Comorbidity Hepatitis C HCV RNA positive HCV RNA negative Stage of disease CD4 nadir < 50 cells/µl 50-199 cells/µl ≥200 cells/µl ART ART use ever Yes No Duration of treatment (months) No ART use ≥ 90 60-89 30-59 <30 Numb er of therapy regimens No ART use <4 e4 Treatment interruptions No ART use Zero e1 Therapy switches in 1 st year No ART use Zero e1 Tenofovir use ever No ART use Yes No

104

Frequencies N= 3147 / 6360 (49,5%)

Model 1 (N = 6360) Univariable regression Multivariable regression* p-value OR (95% CI) p-value OR (95% CI)

1522 / 3182 (47,8%) 1625 / 3178 (51,1%)

0,9 0,8 - 1,0 1

0,008

2293 / 4697 (48,8%) 854 / 1663 (51,4%)

0,9 0,8 - 1,0 1

0,076

0,7 1

0,6 –0,9

<0,001

1262 432 224 1229

/ / / /

(56,0%) (35,4%) (49,1%) (50,6%)

1,2 1,1 - 1,4 <0,001 0,5 0,5 - 0,6 <0,001 0,9 0,8 - 1,2 0,569 1

1,3 0,8 1,2 1

1,2 –1,5 0,6 –0,9 0,9 –1,5

<0,001 0,012 0,144

20 1170 512 1445

/ 60 (33,3%) / 2155 (54,3%) / 938 (54,6%) / 3207 (45,1%)

1,4 1,3 -1,6 <0,001 1,5 1,3 -1,7 <0,001 1

1,4 1,5 1

1,2 –1,6 1,3 –1,8

<0,001 <0,001

438 / 1117 (39,2%) 2709 / 5243 (51,7%)

0,6 0,5 - 0,7 <0,001 1

280 / 1205 (23,2%) 732 / 1949 (37,6%) 2135 / 3206 (66,6%)

0,2 0,1 - 0,2 <0,001 0,3 0,3 - 0,3 <0,001 1

0,1 0,2 1

0,1 –0,1 0,2 –0,2

<0,001 <0,001

2691 / 5374 (50,1%) 456 / 986 (46,2%)

1,2 1,0 - 1,3 1

0,027

456 1455 352 476 408

1,0 1,2 1,0 1,3 1

- 1,2 - 1,4 - 1,3 - 1,6

0,869 0,037 0,687 0,003

1,1 2,8 2,1 1,8 1

0,8 2,2 1,6 1,4

–1,5 –3,5 –2,6 –2,2

0,545 <0,001 <0,001 <0,001

456 / 986 (46,2%) 1682 / 3477 (48,4%) 1009 / 1897 (53,2%)

0,8 0,6 - 0,9 <0,001 0,8 0,7 - 0,9 <0,001 1

0,5 1

0,4 –0,6

<0,001

456 / 986 (46,2%) 1869 / 3415 (54,7%) 822 / 1959 (42,0%)

1,2 1,0 - 1,4 0,027 1,7 1,5 - 1,9 <0,001 1

2,1 1

1,9 –2,5

<0,001

456 / 986 (46,2%) 1882 / 3785 (49,7%) 809 / 1589 (50,9%)

0,8 0,7 - 1,0 1,0 0,8 - 1,1 1

456 / 986 (46,2%) 2007 / 3874 (51,8%) 684 / 1500 (45,6%)

1,0 0,9 - 1,2 0,751 1,3 1,1 - 1,4 <0,001 1

1,4 1

1,2 –1,7

<0,001

/ / / / /

2253 1221 456 2430

986 2872 739 888 875

(46,2%) (50,7%) (47,6%) (53,6%) (46,6%)

0,8 1,0 0,9 1,1

* adjusted for the variables: age, hepatitis C, therapy switches in 1st year

0,021 0,426

105

10.3.2.2 Risk factors for a recent CD4 cell count <200/µl on ART

10.4 HIV RNA (viral load)

This analysis includes all patients currently in care who have been on ART for at least 75 days before the measurement of the viral load.

10.4.1 Last HIV RNA in the patients currently in care regardless of ART

All centres Variable Demographic characteristics Age <45 years ≥45 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Nationality High prevalence countries Low prevalence countries Stage of disease AIDS Yes No ART ART initiation Before 1.1.1997 After 1.1.1997 Numb er of therapy regimens <4 ≥4

Frequencies N= 185 / 3359 (5,5%)

Model 1 (N = 3359) Univariable regression Multivariable regression* p-value OR (95% CI) p-value OR (95% CI)

99 / 1680 86 / 1679

(5,9%) (5,1%)

1,2 1

0,9 –1,6

0,328

128 / 2415 57 / 944

(5,3%) (6,0%)

0,9 1

0,6 –1,2

0,400

/ 1252 (2,8%) / 475 (13,3%) / 189 (6,3%) / 1443 (5,2%)

0,5 2,8 1,2 1

0,3 –0,8 2,0 –4,0 0,7 –2,3

0,002 <0,001 0,508

35 63 12 75

0,5 2,1 1,1 1

0,3 –0,7 1,4 –3,1 0,6 –2,1

87.5% of the patients currently in care (3396 of 3880) have a current HIV RNA below 400 copies/ml.

Last HIV RNA – patients currently in care

0,001 <0,001 0,764

/ 4 / 1308 / 549 / 1498

(0,0%) (4,3%) (5,5%) (6,6%)

0,6 0,8 1

0,5 –0,9 0,5 –1,2

0,008 0,346

17 / 339 168 / 3020

(5,0%) (5,6%)

0,9 1

0,5 –1,5

0,675

103 / 1028 (10,0%) 82 / 2331 (3,5%)

3,1 1

2,3 –4,1

<0,001

3,3 1

2,4 –4,6

<0,001

22 / 501 163 / 2858

(4,4%) (5,7%)

0,8 1

0,5 –1,2

0,236

0,4 1

0,3 –0,8

0,004

115 / 2047 70 / 1312

(5,6%) (5,3%)

1,1 1

0,8 –1,4

0,726

1,7 1

1,1 –2,6

0,012

137 / 2320 48 / 1039

(5,9%) (4,6%)

1,3 1

0,9 –1,8

0,132

22 / 266 163 / 3093

(8,3%) (5,3%)

1,6 1

1,0 –2,6

0,041

19 / 244 166 / 3115

(7,8%) (5,3%)

1,5 1

0,9 –2,5

0,107

0 56 30 99

Therapy switches in 1 year None ≥1 Cumulative resistances NRTI + NNRTI Yes No NRTI+ NNRTI + PI Yes No

* adjusted for the variables: age, gender, population size of area of residence, nationality, therapy switches in 1st year, resistance to NRTI+NNRTI, treatment interruptions

106

107

Proportion of patients with HIV RNA <200, <400 and ≤50 in different periods (patients currently in care)

10.4.3 Risk factors for viral replication The analyses in chapter 14.4.3 include all patients currently in care who have been on ART for at least 75 days before the measurement of the viral load. All centres

10.4.2 Last HIV RNA of patients on ART

108

* since Jan. 2011: at least 75 days between ART initiation and HIV RNA measurement

Variable Demographic characteristics Age <45 years ≥45 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Nationality High prevalence countries Low prevalence countries Stage of disease AIDS Yes No CD4 nadir <50 cells/µl 50-199 cells/µl ≥200 cells/µl ART ART initiation Before 1.1.1997 After 1.1.1997 Numb er of therapy regimens <4 ≥4 Treatment interruptions None ≥1 Treatment switches in 1 st year None ≥1 Cumulative resistances NRTI + NNRTI Yes No NRTI+ NNRTI + PI Yes No

Frequencies N= 109 / 3359 (3,2%)

Model 1 (N = 3359) Univariable regression Multivariable regression* p-value p-value OR (95% CI) OR (95% CI)

70 / 1680 39 / 1679

(4,2%) (2,3%)

1,8 1,2 –2,7 1

0,003

64 / 2415 45 / 944

(2,7%) (4,8%)

0,5 0,4 –0,8 1

0,002

1,6 1

1,0 –2,5

0,035

19 32 11 47

/ / / /

1252 475 189 1443

(1,5%) (6,7%) (5,8%) (3,3%)

0,5 0,3 –0,8 2,1 1,4 –3,4 1,8 0,9 –3,6 1

0,004 0,001 0,078

0,7 1,9 2,2 1

0,4 –1,4 1,1 –3,3 1,1 –4,6

0,329 0,019 0,035

0 39 10 60

/ 4 / 1308 / 549 / 1498

(0,0%) (3,0%) (1,8%) (4,0%)

0,7 0,5 –1,1 0,4 0,2 –0,9 1

0,144 0,019

0,9 0,4 1

0,6 –1,3 0,2 –0,8

0,474 0,012

20 / 339 89 / 3020

(5,9%) (2,9%)

2,1 1,3 –3,4 1

0,004

50 / 1028 59 / 2331

(4,9%) (2,5%)

2,0 1,3 –2,9 <0,001 1

42 / 637 40 / 1142 27 / 1580

(6,6%) (3,5%) (1,7%)

4,1 2,5 – 6,6 <0,001 2,1 1,3 –3,4 0,004 1

3,5 1,9 1

2,0 –5,9 1,1 –3,1

<0,001 0,017

15 / 501 94 / 2858

(3,0%) (3,3%)

0,9 0,5 –1,6 1

0,731

0,4 1

0,2 –0,8

0,007

61 / 2047 48 / 1312

(3,0%) (3,7%)

0,8 0,6 –1,2 1

0,280

47 / 2358 62 / 1001

(2,0%) (6,2%)

0,3 0,2 –0,5 <0,001 1

0,3 1

0,2 –0,5

<0,001

79 / 2320 30 / 1039

(3,4%) (2,9%)

1,2 0,8 –1,8 1

26 / 266 83 / 3093

(9,8%) (2,7%)

3,9 2,5 –6,2 <0,001 1

4,3 1

2,4 –7,6

<0,001

23 / 244 86 / 3115

(9,4%) (2,8%)

3,7 2,3 –5,9 <0,001 1

0,434

* adjusted for the variables: gender, nationality, number of therapy regimens, treatment switches in 1st year

109

RISKS OF ANTIRETROVIRAL THERAPY

11. Risks of antiretroviral therapy

11.2 Frequency of resistance

11.1 Definition of resistance under ART

11.2.1 Frequency of NRTI-associated resistance mutations

The rate of resistance development during antiretroviral therapy („percent with resistance“) corresponds to the number of patients with resistance mutations in relation to the number of patients on ART (see also chapter 8). “Cumulative resistance” includes any mutation ever found in a particular patient. The resistance mutations have been classified according to the “2011 Update of the Drug Resistance Mutations in HIV-1” from the International AIDS-Society-USA (http://iasusa.org/resistance_mutations/mutations_figures.pdf).

11.2.1.1 Overview

All centers

Deceased since 1997, NRTI use

The following codons and amino acids have been classified as resistance (IAS):

Reverse transcriptase NRTI M41 A62 K65 D67 T69 K70 L74 V75 F77 Y115 F116 Q151 M184 L210 T215 K219

112

The table shows the numbers of patients with NRTI-associated resistance mutations among all patients who have ever been treated with Nucleoside Reverse Transcriptase Inhibitors („NRTI“).

L V R N ins R, E V I L F Y M V, I W Y, F Q, E

NNRTI V90 A98 L100 K101 K103 V106 V108 E138 V179 Y181 Y188 G190 H221 P225 F227 M230

I G I H, E, P N, S A, M, I I A, G, K, Q, R D, F, T, L C, I, V L, H, C A, S Y H C I, L

N = 695

Protease L10 V11 G16 K20 L24 D30 V32 L33 E34 M36 K43 M46 I47 G48 I50 F53 I54 Q58 D60 I62 L63 I64 H69 A71 G73 T74 L76 V77 V82 N83 I84 I85 N88 L89 L90 I93

F, R, I, V, C I E R, M, I, T, V I N I I, F, V Q I, L, V T I, L V, A V V, L L, Y V, M, L, T, S, A E E V P L, M, V K, R V, I, T, L S, T, C, A P V I A, T, F, S, I, L D V V D, S V, I, M M L, M

Resistance to NRTI

132 (19,0%)

Patients currently in care and NRTI use ever N = 3616 477 (13,2%)

Codon 41

(6,8%)

195

(5,4%)

Codon 62

(0,4%)

(0,5%)

Codon 65

(0,7%)

(0,8%)

Codon 67

(6,8%)

166

(4,6%)

Codon 69

(0,1%)

Codon 70

(4,6%)

133

(3,7%)

Codon 74

(2,0%)

(1,1%)

Codon 75

(0,3%)

(0,1%)

Codon 77

(0,0%)

(0,1%)

Codon 115

(0,4%)

(0,3%)

Codon 116

(0,1%)

Codon 151

(0,3%)

(0,2%)

Codon 184

99 (14,2%)

333

(9,2%)

Codon 210

(4,6%)

106

(2,9%)

Codon 215

(7,6%)

203

(5,6%)

Codon 219

(4,3%)

(2,2%)

113

11.2.1.2 Risk factors for the resistance mutation K65R of the RT

11.2.2 Frequency of NNRTI-associated resistance mutations

Recruitment for this analysis has been in agreement to entry criteria of COHERE. Additionally, patients who died before 1.1.2000 have been excluded.

The table shows the numbers of NNRTI-associated resistance mutations among patients who have ever been treated with Non-Nucleoside Reverse Transcriptase Inhibitors („NNRTI“).

All centres Variable Demographic characteristics Age <45 years ≥45 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Stage of disease AIDS Yes No CD4 nadir Missing value <50 cells/µl 50-199 cells/µl ≥200 cells/µl ART Ab acavir use ever Yes No Tenofovir use ever Yes No ART initiation Before 1.1.1997 After 1.1.1997

Frequencies N= 40 / 5288 (0,8%)

Univariable regression OR (95% CI) p-value

14 / 2644 26 / 2644

(0,5%) (1,0%)

0,5 1

0,3 –1,0

26 / 3865 14 / 1423

(0,7%) (1,0%)

0,7 1

0,4 –1,3

0,250

10 8 0 22

(0,5%) (0,8%) (0,0%) (1,0%)

0,5 0,8 1

0,2 –1,1 0,4 –1,8 -

0,072 0,601 -

0 13 6 21

/ 1886 / 945 / 361 / 2096

Deceased since 1997, NNRTI use

All centers

N = 427

0,061

Resistance to NNRTI

/ 28 / 1842 / 767 / 2651

(0,0%) (0,7%) (0,8%) (0,8%)

0,9 1,0 1

0,4 –1,8 0,4 –2,5

26 / 1771 14 / 3517

(1,5%) (0,4%)

3,7 1

1,9 –7,2

0 19 17 4

(0,0%) (1,7%) (0,9%) (0,2%)

10,5 5,6 1

/ 36 / 1089 / 1803 / 2360

Model 1 (N = 5288) Multivariable regression* OR (95% CI) p-value

0,743 0,978

<0,001

3,5 –30,8 <0,001 1,9 –16,7 0,002

17 / 1890 23 / 3398

(0,9%) (0,7%)

1,3 1

0,7 –2,5

37 / 3896 3 / 1392

(0,9%) (0,2%)

4,4 1

1,4 –14,4

0,013

8 / 804 32 / 4484

(1,0%) (0,7%)

1,4 1

0,6 –3,0

0,399

9,5 5,0 1

3,2 –28,7 1,7 –15,1

<0,001 0,004

0,372

4,7 1

1,4 –15,6

88 (20,6%)

Patients currently in care and NNRTI use ever N = 2330 307 (13,2%)

Codon 90

(0,2%)

(0,6%)

Codon 98

(2,3%)

(0,9%)

Codon 100

(0,2%)

(0,5%)

Codon 101

(4,2%)

(1,7%)

Codon 103

48 (11,2%)

172

(7,4%)

Codon 106

(1,9%)

(1,1%)

Codon 108

(3,0%)

(1,7%)

Codon 138

(0,5%)

Codon 179

(0,9%)

Codon 181

(8,7%)

106

(4,5%)

Codon 188

(1,4%)

(0,8%)

Codon 190

(4,2%)

(3,0%)

Codon 221

(0,7%)

(0,9%)

Codon 225

(0,7%)

(0,3%)

Codon 227

(0,0%)

Codon 230

(0,2%)

0,011

* adjusted for the variables: age, gender, mode of transmission, population size of area of residence, Abacavir use ever, ART initiation

114

115

11.2.3 Frequency of PI-associated resistance mutations The table shows the numbers of the PI-associated resistance mutations among patients who have ever been treated with Protease Inhibitors (â&#x20AC;&#x17E;PIâ&#x20AC;&#x153;).

Major mutations:

N = 533

Any minor resistance to PI

195 (36,6%)

206

(7,8%)

Codon 30

(1,3%)

(1,2%)

Codon 32

(0,8%)

(0,4%)

Codon 46

(5,8%)

(3,7%)

Codon 47

(0,8%)

(0,5%)

801 (30,3%)

Codon 48

(0,6%)

(0,4%)

Patients currently Deceased since in care and 1997, PI use PI use ever N = 533

Patients currently in care and PI use ever N = 2645

67 (12,6%)

Any major resistance to PI

Minor mutations:

All centers

N = 2645

Codon 10

(9,8%)

219

(8,3%)

Codon 50

(0,2%)

(0,1%)

Codon 11

(0,4%)

(0,2%)

Codon 54

(4,5%)

(2,3%)

Codon 16

(0,2%)

(1,1%)

Codon 58

(0,6%)

(0,5%)

Codon 20

(6,0%)

143

(5,4%)

Codon 74

(0,0%)

(0,1%)

Codon 24

(0,4%)

(0,6%)

Codon 76

(0,0%)

Codon 33

(2,1%)

(2,3%)

Codon 82

(4,3%)

(3,2%)

Codon 34

(0,0%)

Codon 83

(0,2%)

(0,0%)

Codon 84

(2,4%)

(1,0%)

Codon 88

(1,3%)

(1,1%)

Codon 90

(6,6%)

(3,7%)

Codon 36

82 (15,4%)

348 (13,2%)

Codon 43

(0,2%)

Codon 53

(0,4%)

(0,7%)

Codon 60

(0,8%)

(0,9%)

Codon 62

(1,9%)

(3,3%)

Codon 63

143 (26,8%)

11.2.4 Resistance to single or multiple drug classes

All centres

461 (17,4%)

Codon 64

(0,8%)

(2,8%)

Codon 69

(1,1%)

(3,4%)

Codon 71

78 (14,6%)

222

(8,4%)

Codon 73

(2,1%)

(0,9%)

Codon 77

61 (11,4%)

252

(9,5%)

Codon 85

(0,0%)

(0,1%)

Codon 89

(0,8%)

(1,4%)

Codon 93

(2,6%)

121

(4,6%)

Deceased since 1997, ever ART N = 703

Resistance test available Wild type

116

Deceased since 1997, PI use

All centers

274 (39,0%) 25

(3,6%)

Patients currently in care and ever ART N = 3644 1014 (27,8%) 84

(2,3%)

"Any" resistance

249 (35,4%)

930 (25,5%)

NRTI

134 (19,1%)

477 (13,1%)

NNRTI

100 (14,2%)

351

227 (32,3%)

863 (23,7%)

NRTI and PI

115 (16,4%)

421 (11,6%)

NRTI and NNRTI

74 (10,5%)

265

(7,3%)

NNRTI and PI

93 (13,2%)

317

(8,7%)

3-class-resistance

70 (10,0%)

242

(6,6%)

(9,6%)

117

118

Up to 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Federal state Burgenland Carinthia Lower Austria Upper Austria Salzburg Styria Tyrol Vorarlberg Vienna Foreign countries Missing value Total

Year of ART initiation

All patients

136 395

259

239 156

1887 716

1302 2603

97 81 12 205

975 354 128 1146

1301

1 130 75 189

5 988 388 1222

e 33 years Total

45 44 36 37 45 37 38 26 33 29 15 10

Resistance test available 111 128 133 155 167 188 222 228 265 302 324 380

Number of patients

14 33 86 151 62 56 128 42 433 8 1 1014

54 134 361 414 188 304 377 109 1647 37 19 3644

< 33 years

> 1 million Mode of transmission MSM IDU Others Heterosexual Gender Men Women Age at time of HIV-test

â&#x2030;Ľ 100 000

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Population size of area of residence Missing value < 100 000

Year of ART initiation

Patients who initiated ART after 2000

245 112 86 59 59 58 45 44 36 37 45 37 38 26 33 29 15 10

Resistance test available

333 178 148 130 128 124 111 128 133 155 167 188 222 228 265 302 324 380

Number of patients

19 51

31 20

16 7 2 26

20 7 24

7 6 5 3 2 4 1 3 7 6 3 4

Wild type

0 2 5 12 7 7 5 4 41 1 84

5 5 9 6 3 5 7 6 5 3 2 4 1 3 7 6 3 4

Wild type

117 344

227

208 136

81 74 10 179

1 110 68 165

38 38 31 34 43 33 37 23 26 23 12 6

Any resistance

14 31 81 139 55 49 123 38 392 7 1 930

240 107 77 53 56 53 38 38 31 34 43 33 37 23 26 23 12 6

Any resistance

44 102

68 34

23 11 5 63

44 26 32

14 17 7 8 14 5 9 9 8 3 6 2

NRTI

7 12 45 94 27 26 79 15 167 4 1 477

197 74 36 25 20 23 14 17 7 8 14 5 9 9 8 3 6 2

NRTI

39 107

70 37

31 19 4 53

44 23 40

11 13 7 12 12 9 8 10 11 6 5 3

NNRTI

4 6 38 59 27 23 36 8 144 5 1 351

120 41 31 17 18 17 11 13 7 12 12 9 8 10 11 6 5 3

NNRTI

111 329

218

201 128

74 74 10 171

1 103 66 159

38 38 30 33 41 32 36 23 23 20 10 5

41 94

65 29

20 11 5 58

40 25 29

14 17 7 7 13 4 8 9 7 3 4 1

Resistance to NRTI and PI PI

13 28 75 126 52 47 114 32 371 5 863

216 100 71 48 49 50 38 38 30 33 41 32 36 23 23 20 10 5

6 9 41 82 24 25 71 9 152 2 421

173 68 31 20 15 20 14 17 7 7 13 4 8 9 7 3 4 1

NRTI and PI

Resistance to

23 58

40 18

16 5 3 34

25 14 19

7 11 3 4 7 2 5 6 6 1 4 2

NRTI and NNRTI

34 93

63 30

24 19 4 46

37 21 35

11 13 6 12 10 8 7 10 8 3 3 2

NNRTI and PI

3 5 28 52 18 18 28 4 104 4 1 265

112 38 24 14 7 12 7 11 3 4 7 2 5 6 6 1 4 2

NRTI and NNRTI

21 48

37 14

13 5 3 30

21 13 17

7 11 3 4 6 1 4 6 5 1 0

3 3 28 44 17 18 27 2 98 2 242

105 36 22 11 6 11 7 11 3 4 6 1 4 6 5 1 2 1

3-classresistance

4 4 36 50 26 22 34 6 132 3 317

113 38 28 14 15 16 11 13 6 12 10 8 7 10 8 3 3 2

NNRTI and PI

11.2.5 Resistance according to demographic characteristics

119

11.2.6 Cumulative resistance related to different time periods of ART initiation Initial therapy before 1.1.1997 N No resistance test after ART

Initial therapy between 1.1.1997 and 31.12.1999 N 199

% 49,9%

Initial therapy after 1.1.2000 N 2249

11.2.7 Probability of development of resistance 11.2.7.1 Any ART regimen „Any“ resistance

3-class-resistance

153

30,0%

83,7%

Resistance test after ART

357

70,0%

200

50,1%

439

16,3%

Total

510

100%

399

100%

2688

100%

11,8%

Number of NRTI-associated resistance mutations 0 mutations

16,9%

119

29,8%

316

1 mutation

10,6%

9,0%

3,0%

2 mutations

6,7%

3,8%

0,8%

3 mutations

9,0%

2,5%

0,4%

4 mutations

10,2%

2,8%

0,3%

5 mutations

9,2%

2,3%

0,0%

11,8%

6 mutations

4,1%

7 mutations

2,4%

8 mutations

0,8%

9 mutations

0,2%

11.2.7.2 Any ART regimen and initial ART after January 1, 1997 „Any“ resistance

3-class-resistance

Number of NNRTI-associated resistance mutations 0 mutations

196

38,4%

134

33,6%

316

1 mutation

13,5%

7,5%

2,7%

2 mutations

9,8%

7,0%

1,3%

3 mutations

4,7%

1,5%

0,6%

4 mutations

1,8%

0,5%

0,0%

5 mutations

0,6%

6 mutations

0,8%

0,4%

7 mutations

11.2.7.3 Initial ART with 2 NRTI + 1 NNRTI Resistance to NNRTI

Resistance to NRTI

Number of PI-associated resistance mutations

120

0 mutations

8,0%

9,0%

2,6%

1 mutation

14,5%

10,8%

3,2%

2 mutations

13,7%

13,0%

3,5%

3 mutations

8,6%

7,3%

2,4%

4 mutations

4,1%

4,8%

2,5%

5 mutations

3,9%

2,0%

1,3%

6 mutations

4,7%

2,0%

0,3%

7 mutations

3,5%

0,0%

0,1%

8 mutations

1,4%

0,5%

0,2%

9 mutations

1,2%

0,3%

0,1%

10 mutations

1,6%

0,0%

11 mutations

1,4%

0,5%

0,0%

12 mutations

0,8%

0,0%

13 mutations

0,6%

0,0%

14 mutations

1,4%

0,0%

15 mutations

0,2%

16 mutations

0,2%

20 mutations

0,2%

11.2.7.4 Initial ART with 2 NRTI + 1 PI Resistance to PI

Resistance to NRTI

121

122

Age (years; mean ± S. D.) Federal states Carinthia Upper Austria Salzburg Styria Tyrol Other federal states Foreign countries Vienna Gender Men Women Mode of transmission MSM IDU Others/missing value Hetero AIDS CD4 nadir (cells/µl; mean ± S. D.) Current CD4 cell counts (cells/µl; mean ± S. D.) Last HIV-RNA log10 copies/ml (mean ± S. D.) < 400 copies/ml d 50 copies/ml Duration of ART (months; mean ± S. D.)

3 44 17 18 27 33 2 98 (1,2%) (18,2%) (7,0%) (7,4%) (11,2%) (13,6%) (0,8%) (40,5%)

181 61 (74,8%) (25,2%)

89 (36,8%) 30 (12,4%) 23 (9,5%) 100 (41,3%) (56,2%) 136 112,6 ± 105,2 580,8 ± 300,5

Patients currently in care and ART use ever N = 242

49,4 ± 10,3

1,0 1,9 1

3,3 1

(6,6%) (5,6%) (11,0%) (6,4%) (0,0%) (5,9%) (10,6%) (5,9%)

(12,5%) (4,1%) (0,0%) (13,8%) (8,3%) (2,8%) (0,0%) (6,4%) (10,1%) (9,3%)

(27,6%) (8,8%) (1,4%)

/ 1347 / 535 / 210 / 1552 / 6 / 1400 / 583 / 1655

/ 16 / 3359 / 129 / 140

0 82 62 98

136 / 1085 106 / 2559 / 11 / 667 / 1210 / 1756

89 30 23 100

0 92 101 49 0 216 13 13

141 / 511 68 / 769 33 / 2364

26,9 6,9 1

0,7 1,1 1

5,6 3,2 1

1,0 0,9 1,8 1

1,2 1

(6,9%) (5,9%)

18,1 –39,9 4,5 –10,5

0,4 –1,2 0,5 –2,5

<0,001 <0,001

0,184 0,826

<0,001 <0,001

<0,001

2,5 –4,3

3,9 –8,0 2,2 –4,5

0,940 <0,001

0,858 0,491 0,017

0,8 –1,4 0,6 –1,3 1,1 –2,9

0,7 –1,3 1,4 –2,6

0,287

0,9 –1,6

0,007 0,457

<0,001 <0,001

0,2 –0,8 0,6 –3,7

0,4 1,4 1

26,4 17,0 –41,1 6,4 4,1 –9,9 1

<0,001 <0,001

0,582 0,002

2,3 –5,0 1,4 –2,9

0,6 –1,3 1,3 –2,7

0,9 1,8 1

0,414 0,003 0,908

3,4 2,0 1

0,6 –1,2 0,3 –0,8 0,5 –1,7 0,9 0,5 1,0 1

Model 1 (N = 3644) Multivariable regression* p-value OR (95% CI)

(6,6%)

181 / 2617 61 / 1027

242

*adjusted for the variables: age, gender

3-class-resistance

(15,3%) <0,001

(8,7%)

0,3 –0,5

(7,4%)

0,4 1

70 N = 3644

(3,8%) (9,5%)

N = 177

69 / 1822 173 / 1822

N = 333

Patients currently in care and ART use ever

Variable Demographic characteristics Age <45 years ≥45 years Gender Male Female Mode of transmission MSM IDU Other Heterosexual Population size of area of residence Missing value < 100 000 ≥ 100 000 > 1 million Stage of disease AIDS Yes No CD4 nadir Missing value <50 cells/µl 50-199 cells/µl ≥200 cells/µl Current HIV RNA Missing value < 400 copies/ml 400-9999 copies/ml e 10000 copies/ml ART ART initiation Before 1.1.1997 1.1.1997 to 31.12.2002 Since 1.1.2003

N = 942

AIDS related deaths after 1996 and ART > 6 months

Univariable regression p-value OR (95% CI)

3-class-resistance AIDS related deaths after 1996

Frequencies N= (6,6%) 242 / 3644

All centres All deaths after 1996

All centres

11.2.8 Patients with 3-class-resistance 11.2.8.2 Risk factors for the development of 3-class-resistance

11.2.8.1 3-class-resistance in different populations

1,8 ± 0,9 216 (89,3%) 194 (80,2%) 186,8 ± 60,6

123

11.3 Comorbidities and Comedication

11.3.2 Comedication

11.3.1 Comorbidities

Current therapies

One aim of the Austrian HIV Cohort Study is to document comorbidities and adverse drug reactions, as well as to investigate possible associations with ART. As a first step, important co-morbidities are illustrated.

Cumulative incidence in patients currently in care (comorbidities ever documented)

Austria without Western Austria

N = 565

Acetylsalicylic acid

191

(5,8%)

(14,0%)

ACE inhibitors/ angiotensin antagonists

447

(13,5%)

(14,9%)

Beta blocker

259

(7,8%)

(5,3%)

473

(14,3%)

120

(21,2%)

Statin

429

(12,9%)

123

(21,8%)

Coronary heart disease

105

(3,2%)

(7,8%)

Fibrate

(2,2%)

(0,7%)

Myocardial infarction

(1,9%)

(3,7%)

Insulin

(1,2%)

(1,6%)

Stroke

(1,3%)

(2,7%)

Oral antidiabetic drugs

(2,5%)

(1,2%)

Diabetes mellitus type I

(0,2%)

(0,4%)

Proton pump inhibitors

557

(16,8%)

(15,4%)

Diabetes mellitus type II

144

(4,3%)

(4,1%)

Bisphosphonates

(2,8%)

(6,0%)

CIN II or CIN III or carcinoma in situ1

(8,0%)

(18,2%)

Thyroid hormones

108

(3,3%)

(12,6%)

Invasive cervical cancer1

(1,9%)

(0,0%)

Opiat substitution

374

(11,3%)

(12,9%)

St. p. hysterectomy 1

(3,9%)

(12,7%)

Psychotropic drugs

843

(25,4%)

184

(32,6%)

Anal intraepithelial neoplasia II, III2

(2,8%)

(15,0%)

Anxiolytics, hypnotics, sedatives

310

(9,4%)

(14,7%)

Anal cancer (MSM)2

(1,7%)

(2,9%)

Antidepressants

512

(15,4%)

115

(20,4%)

203

(6,1%)

(17,3%)

Antipsychotics

242

(7,3%)

(8,0%)

Chronic hepatitis B3

(2,7%)

379

(11,4%)

(14,9%)

HCV-related liver cirrhosis

(0,9%)

(5,8%)

Proton pump inhibitors

Attempted suicide or suicide

(1,4%)

(4,6%)

Drug overdose (mainly opiates)

(0,5%)

(3,4%)

392

(11,8%)

(16,1%)

Renal failure stage 3, 4, 5 (current)

172

(5,2%)

(9,7%)

Renal failure stage 3, 4, 5 (ever)

452

(13,6%)

188

(33,3%)

Opiate dependency 3

N = 3315

Western Austria

Hypertension

Chronic hepatitis C

N = 565

N = 3315

Osteoporosis

Western Austria

Austria without Western Austria

Previous and/or current therapies

Austria without Western Austria N = 3315

Western Austria N = 565

1065

(32,1%)

303

(53,6%)

Bisphosphonates

159

(4,8%)

(13,5%)

Antidepressants

861

(26,0%)

235

(41,6%)

Antipsychotics

414

(12,5%)

(16,8%)

Comparison of “co-medications” used by the different medical subspecialities

Percentage related to women [912 in Austria without Western Austria (165 in Western Austria)] Percentage related to MSM [1260 in Austria without Western Austria (206 in Western Austria)] Number related to current diseases

Renal failure ≥ stage 3

Currently Tenofovir N = 2438

Currently Abacavir N = 788

Chi-square p-value

Current renal failure (N=227)

<0,001

Previous and/or current renal failure (N=640)

278

211

<0,001

124

125

11.3.3 Comorbidities related to age

11.3.4 Comedication related to age

Cumulative incidence (Comorbidities ever documented)

Age < 50 years

Hypertension

N = 1222

N = 2658

(8,8%)

360

(29,5%)

Age e 50 years

Coronary heart disease

(1,3%)

115

(9,4%)

ACE inhibitors/ angiotensin antagonists

Myocardial infarction

(0,8%)

(5,1%)

Beta blocker

Stroke

(0,6%)

(3,4%)

Diabetes mellitus type I

(0,1%)

Diabetes mellitus type II

(1,6%)

CIN II or CIN III or carcinoma in situ1

Invasive cervical cancer

(2,3%)

210

(17,2%)

171

(6,4%)

360

(29,5%)

(3,7%)

190

(15,5%)

Statin

166

(6,2%)

386

(31,6%)

(0,3%)

Fibrate

(1,2%)

(3,5%)

124

(10,1%)

Insulin

(0,5%)

(3,1%)

(9,8%)

(8,8%)

Oral antidiabetic drugs

(1,0%)

(5,2%)

(1,5%)

(1,8%)

Proton pump inhibitors

370

(13,9%)

274

(22,4%)

St. p. hysterectomy 1

(3,0%)

(11,7%)

Bisphosphonates

(1,2%)

(7,8%)

Anal intraepithelial neoplasia II, III2

(3,9%)

(5,9%)

Thyroid hormones

(2,7%)

108

(8,8%)

Anal cancer (MSM)

(1,4%)

(3,2%)

Opiat substitution

342

(12,9%)

105

(8,6%)

Osteoporosis

(3,4%)

210

(17,2%)

Psychotropic drugs

667

(25,1%)

360

(29,5%)

Chronic hepatitis B3

(3,0%)

(2,0%)

Anxiolytics, hypnotics, sedatives

265

(10,0%)

128

(10,5%)

Chronic hepatitis C3

327

(12,3%)

136

(11,1%)

Antidepressants

407

(15,3%)

220

(18,0%)

HCV-related liver cirrhosis

(1,2%)

(2,6%)

Antipsychotics

203

(7,6%)

(6,9%)

Attempted suicide or suicide

(1,8%)

(2,0%)

Drug overdose (mainly opiates)

(1,0%)

(0,8%)

374

(14,1%)

109

(8,9%)

(2,9%)

150

(12,3%)

262

(9,9%)

378

(30,9%)

Opiate dependency Renal failure stage 3, 4, 5 (current)3 Renal failure stage 3, 4, 5 (ever)

Acetylsalicylic acid

N = 1222

Age < 50 years

Median age: 39.6 years Median age: 56.2 years

233

Current therapies

Median age: 39.6 years Median age: 56.2 years N = 2658

Age e 50 years

Percentage related to women [794 <50 years, 283 â&#x2030;Ľ50 years] Percentage related to MSM [1024 <50 years, 442 â&#x2030;Ľ50 years] Number related to current diseases

126

127

11.3.5 Lipid metabolism abnormalities (patients currently in care) Total cholesterol HDL-cholesterol

N = 201

N = 3458

N = 198

N = 3364

LDL-cholesterol Triglycerides

N = 194

N = 3276

N = 201

N = 3480

HbA1c "Quality control" LDL cholesterol measured

128

N = 43

N = 795

3470 / 3880

89,4%

LDL>160 mg/dl

380 / 3470

11,0%

LDL>160 mg/dl and no statin

298 /

380

78,4%

Smoking explored

2617 / 3880

67,4%

Smoking

1290 / 2617

49,3%

LDL>160 mg/dl and smoking

131 / 1290

10,2%

LDL>160 mg/dl and smoking and no statin

102 /

77,9%

Coronary heart disease (CHD)

149 / 3880

3,8%

CHD and LDL cholesterol measured

135 /

149

90,6%

CHD and LDL>130

30 /

135

22,2%

Diabetes and HbA1c>8

13 /

174

7,5%

Diabetes and no recent HbA1c

96 /

174

55,2%

131

SUMMARY

12. Summary

Is the HIV test used efficiently?

HIV Patient Management System

Austria has one of the highest rates of HIV tests per capita in Europe. Nevertheless, a substantial number of patients (28.0%) is already immune deficient (CD4 cell count <200/µl) at the time of the first contact with an HIV centre.

A special software, the HIV Patient Management System, is the common tool for the HIV Cohort. The data input is done decentralized in the HIV centres. The input of laboratory results is done mostly electronically, and in every centre various professional groups are involved in data entry. Before data is merged, the cohort participants have been made anonymous. Therefore, it is very laborious to identify cohort participants who are/ were treated in more than just one treatment centre. This cannot be done by the use of personal data such as initials, birthday or postal code, but with HIV specific data (date of the HIV test, CD4 cell counts etc.). On the one hand, the HIV Patient Management System fulfills complex tasks for the clinical management of HIV infected patients, and on the other hand it allows queries and analyses to be performed by the users without restrictions. However, to allow both individual patient management and scientific queries is an enormous challenge which scientific HIV cohorts in other countries have not had to deal with. In Austria, there was no acceptance for a purely scientific data base. While for the clinical patient management the focus is on readability of diagnoses and therapies, creation of medical reports, prescriptions (trade names!), print-out of results etc., scientific queries need precise coding and categorization. Furthermore, the optimization of individual patient management requires an ongoing adjustment to the progress of information technology, whereas purely scientific data bases do not have such technological renewal pressure. Problems due to inadequate input of data concerning coinfections and non-AIDS-defining diseases are most obvious. The HIV Patient Management System also allows the documentation of these diseases without a clear attribution (e. g. ICD-code).

Patients currently in care The highest number of cohort participants are treated at the AKH Vienna (31.6%), followed by the OWS Vienna (24.1%), Innsbruck (14.6%), Linz (11.6%), Graz (8.9%), Salzburg (5.8%), and Klagenfurt (3.4%). However, a considerable portion (25.6%) of patients did not have a follow-up within the last 12 months. Reasons for this „loss of follow-up“ could be missing entry of patient data, multiple entry of individual patients in more than one centre, a change to health-care providers outside the HIV-centres of AHIVCOS and/or lack of knowledge of death.

Who and how many are infected with HIV in Austria? The cohort study records the number of the included patients, the number of patients on ART (approximately 85% of all patients on ART in Austria are included in the cohort), the number of “late“ presenters and finally the number of the patients who died with or without AIDS. We estimate that there are currently about 7500 8500 HIV infected persons living in Austria. The median age at the diagnosis lies between 30 and 40 years since 1990. 27.8% of the patents with a follow-up in the last 12 months are female. The rate is highest in Upper Austria (35.5%) and Vorarlberg (33.3%). In the subgroup of the heterosexually infected, the rate of the women is 51.5%. It is highest in Upper Austria (56.6%), Vienna (52.4%) and Vorarlberg (52.2%). Among patients newly diagnosed in 2012, 34.6% have been infected through heterosexual contacts. Since 2000, 41.4% of newly diagnosed HIV infections were transmitted through heterosexual contacts. Most of the cohort participants are Austrian nationals (74.6%). 9.6% come from high prevalence countries and 12.6% from low prevalence countries outside Austria. Information on the nationality of the remaining patients is missing. 132

Therefore, risk factors for an “early“ and a “late“ diagnosis have been evaluated. Patients who have been diagnosed with HIV between 2001 and 2012 were analysed. During this period, 3754 HIV infections were diagnosed (75.2% male, 24.8% female). The infections occurred in 41.3% through heterosexual transmission, in 37.1% through MSM and in 14.8% through IDU. An “early“ diagnosis is defined by: a seroconversion illness HIV infection (westernblot pattern or antigen/HIV RNA with corresponding clinical symptoms) or documented seroconversion with negative test not more than 3 years before the first positive HIV test. A “late“ diagnosis is defined by: CD4<350 at time of HIV diagnosis and/or AIDS within 3 months of HIV diagnosis. An “advanced“ diagnosis is defined by: CD4<200 at time of HIV diagnosis and/or AIDS within 3 months of HIV diagnosis. 15.9% of the examined patients had an “early“ diagnosis, 49.7% a “late“ diagnosis and 28.9% had an “advanced” diagnosis. A higher risk to be diagnosed “late” was found in older patients, in those who have been infected heterosexually, persons with a population size of the area of residence below 100 000 inhabitants and in persons originating from high prevalence countries. The results were much the same for an “advanced” diagnosis, with the exception that persons with a population size of the area of residence below 100 000 were not affected. An „early“ diagnosis was found more frequently in younger patients, MSM and IDU, in patients originating from Austria or other low prevalence countries and in persons with a population size of the area of residence below 1 million inhabitants. Thus, about half of the patients are diagnosed late and nearly a third of patients are diagnosed „advanced“, and this has not changed in the last years (see also chapter 6).

Transmission of drug resistant HIV („resistance before therapy“) In all centres, 166 (7.2%) of 2299 patients (in the CASCADE centres: 125 of 1626 patients; 7.7%) were identified who had at least one resistance mutation before their first antiretroviral therapy. In the CASCADE-centres, one patient had a 3-class resistance to NRTI, NNRTI and PI before starting ART. Six patients had a resistance to NRTI and PI, two patients had a resistance to NRTI and NNRTI, and three patients had a resistance to NNRTI and PI. The transmission of drug resistant HI viruses has decreased in the last years. However, not all centres did resistance tests before ART initiation or at diagnosis, but most have implemented the routine testing in 2003.

Stage of HIV disease The cohort participants represent all stages of HIV infection. Half of the patients have a CD4 nadir <200/µl. The median of the CD4 nadir of the patients currently in care is 204/µl. The current CD4 cell count is 571/µl (median at the last measurement). As of January 1st, 2013, 247 (6.3%) of the patients currently in care had a current CD4 cell count below 200/µl and only 44 (1.1%) of them had a CD4 cell count <50/µl. The mean CD4 cell count is currently 601/µl. Therefore the number of patients with an opportunistic infection will remain low in the following years. 133

Mortality The reduction of mortality after the implementation of antiretroviral combination therapies is impressive (see items 10.1 and 10.2). In 1994, the death rate of patients with AIDS was 47.0 per 100 person-years for men and 55.0 for women. Over the last years the rate decreased to below 10 for men and to below 5 for women. From 2005 to 2010 (except for the year 2006), injecting drug users had a higher death rate than homosexual men. Only in 2006 the death rate of homosexual men was higher than for IDU. Factors associated with increased mortality after the diagnosis AIDS include age below 45 years as well as transmission through MSM or IDU, a CD4 nadir below 200 cells/µl and residence in a metropolitan area with more than 1 million inhabitants. Moreover, mortality was higher when AIDS was diagnosed in the earlier years of the epidemic (especially before 1995).

Viral suppression under antiretroviral therapy

000 and 1 million inhabitants. Persons with a current HIV RNA below 400 copies/ml and persons infected through IDU (compared to all other modes of transmission) seemed to have a lower risk for development of 3-class-resistance during ART. In our cohort, 40 patients of 5288 (0.8%) have a mutation of the codon 65 of the RT (K65R). The occurrence of the mutation K65R was more frequent in regimens including Tenofovir compared with Abacavir and could be found more often in patients with advanced immune deficiency (low CD4 nadir/ AIDS; chapter 11.2.1.2).

Coinfections Coinfections with syphilis, hepatitis B and hepatitis C are common. Like in other European countries, an enormous increase of new syphilis infections, especially among homosexual men, is apparent. This indicates a lack of prevention and neglection of “Safer Sex” practices.

The rate of viral suppression under antiretroviral therapy in Austria is similar to figures from other countries. However, it has to be considered that the rate of viral suppression has been measured with the patients currently in care and that patients with “loss of follow-up“ are not included.

In Austria, infection with hepatitis C is uncommon in homosexual men. This supports the assumption that the transmission of hepatitis C mainly happens in special circumstances, e.g. parenteral drugs, trauma. Not all patients were offered vaccination against hepatitis B, although it is recommended for all HIV infected persons.

Increase of CD4 cell counts during antiretroviral therapy

Comorbidity

The CD4 cells during antiretroviral therapy have continuously increased, and the increase continues after 5 and 7.5 years of ART initiation. The increase is faster in patients on continuous ART compared to patients with treatment interruptions (see item 10.3.2).

A relatively high number of patients is suffering from other chronic diseases, such as psychiatric disorders (especially depression), osteoporosis, and diabetes. Of special concern are cardiovascular diseases and the risk of myocardial infarctions. Unfortunately, data entry regarding comorbidities is still incomplete in some centres. The improvement of data entry is one of the challenges for the Austrian HIV Cohort Study.

Access to antiretroviral therapy In general the Austrian HIV Cohort Study cannot evaluate if the access to the HIV centres differs by gender, mode of transmission, nationality or other factors and whether these influence the access to antiretroviral therapy. The HIV Cohort Study data show the following picture: A minority of the study participants does not originate from Austria. About 33% of the heterosexually infected persons are non-Austrian nationals. The access to antiretroviral therapy for persons originating from high prevalence countries appears more difficult than for Austrians (see chapter 9.9). Injecting drug users and patients from high prevalence countries are less likely to be on ART. Patients living in a city or village with less than 1 million inhabitants are more likely to be on ART. The seven HIV centres have to care for an increasing number of patients on antiretroviral treatment. This was a natural development, there was no public health policy which pushed the treatment into the HIV-centres. One might say, “the market wants it that way“.

Outlook The report of the Austrian HIV Cohort Study has become more comprehensive in recent years. Therefore, the current report can be compared well to other reports (e.g. report of renal therapy of the Austrian Society for Nephrology and Austrotransplant). Moreover, the establishment of the HIV Patient Management System has improved clinical care for persons with HIV/AIDS („Good Clinical Chronic Disease Practice“). But it was also clear that shortcomings of the Austrian HIV Cohort Study would become more obvious. A lot of problems are due to inconsistent use of the HIV Patient Management System with the corollary of inconsistent data entry into this software. Regular updates and improvements of the HIV Patient Management System should help to face these challenges. The development of the HIV Patient Management System incorporated the international standard format, the HIV Cohorts Data Exchange Protocol (HICDEP), so that data merging with networks of cohorts like ART-CC, CASCADE and COHERE has been and will be greatly facilitated.

Development of resistances during antiretroviral therapy The probability of developing resistance to antiretroviral drugs seems to be decreasing (chapter 11.2.7). So, the risk of „any“ resistance after more than 10 years of ART is about 48%, for NRTI-associated resistance about 20% and for 3-class resistance 10%. The probability of NNRTI-associated resistance after more than 10 years is 20% in patients who started ART with NNRTIs. The probability of PI-associated resistance after 10 years is 45% in patients who had a PI-based antiretroviral combination therapy as their initial therapy. The results are about the same if transmitted resistances are excluded. The strongest risk factor for the development of 3-class-resistance during antiretroviral therapy is initiation of ART before 1997, followed by low CD4 nadir and a population size of the area of residence between 100 134

135

13. Glossary

14. Austrian HIV Cohort Study Group

A Ab ACE AGES AHIVCOS ART ARVs ATC-Code B betw. BMG C cART CDC CIN CIS ECDC EuroHIV GP HBA1c HBV HCV HDL Hetero HIP IAS ICD IDU INSTI Interm. CHD LA LDL m. MI MSM N.a. n.s. neg. NNRTI NRTI OWS P PI RNA RT S SD/ s.d. St St. p. T UA UK Vertical Vie Vo WHO ys.

As of April 2013

136

Austria Antibody Angiotensin-converting enzyme Austrian Agency for Health and Food Safety Austrian HIV Cohort Study Antiretroviral therapy (HIV-therapy) Antiretrovirals Anatomical therapeutic-chemical code Burgenland between Federal Ministry of Health Carinthia Combination antiretroviral therapy Centers for Disease Control Cervical intraepithelial neoplasia Commonwealth of Independent States European Centre for Disease Prevention and Control European Centre for the Epidemiological Monitoring of AIDS General practitioner Hemoglobin A1c Hepatitis B virus Hepatitis C virus High density lipoprotein Heterosexually acquired infection HIV-Patient-Management-System International AIDS-Society International Classification of Diseases (WHO) Injecting drug users Integrase strand transfer inhibitor Intermediate Coronary heart disease Lower Austria Low density lipoprotein month(s) Myocardial infarction Men who have sex with men Not available/ not applicable not significant negative Non Nucleoside Reverse Transcriptase Inhibitor Nucleoside Reverse Transcriptase Inhibitor Otto-Wagner-Spital Wien/Otto-Wagner Hospital Vienna Protease Protease inhibitor Ribonucleic acid Reverse transcriptase Salzburg Standard deviation Styria Status post Tyrol Upper Austria United Kingdom Vertical transmission Vienna Vorarlberg World Health Organization years

Steering committee members: Alexander Egle, Maria Geit, Bernhard Haas, Manfred Kanatschnig, Armin Rieger, Andrea Steuer, Robert Zangerle Coordinating Centre: University Hospital Innsbruck (Robert Zangerle) Funding: Austrian Agency for Health and Food Safety (AGES), Hospitals running HIV treatment centres, pharmaceutical companies (all involved in marketing HIV drugs provide equal contributions, irrespective of their market shares) HIV treatment centres, *site coordinating physicians: (LKH Innsbruck) Martin Gisinger, Maria Kitchen, Elisabeth Rieser, Brigitte Rühr, Mario Sarcletti*, Robert Zangerle. (LKH Salzburg) Alexander Egle, Richard Greil*, Michaela Schachner, Ninon Taylor. (AKH Linz) Maria Geit*, Angela Öllinger. (AKH Vienna) Regina Aichwalder, Florian Breitenecker, Katharina Grabmeier, Armin Rieger*, Veronique Touzeau. (Otto-Wagner Hospital Vienna) Piotr Cichon, Manfred Gartner, Brigitte Schmied, Andrea Steuer*. (LKH Graz West) Bernhard Haas*, Andreas Kapper. (LKH Klagenfurt) Manfred Kanatschnig*. Virology: Elisabeth Puchhammer-Stöckl (Vienna) Data management: Heinz Appoyer (IT-related), Stefanie Gogl (AHIVCOS), Gisela Sturm (AHIVCOS) Data safety and protection: Klaus Schindelwig (Innsbruck) Scientific advisory board: Bruno Ledergerber (Zurich), Gerd Fätkenheuer (Cologne)

Verein Österreichische HIV-Kohortenstudie c/o Univ.-Prof. Dr. Robert Zangerle HIV-Bereich Universitätsklinik für Dermatologie und Venerologie Anichstraße 35 6020 Innsbruck Tel.: +43/(0)512/504-23021 E-Mail: HIV.Kohorte@uki.at

AUTHORS: Martin Gisinger Stefanie Gogl Maria Kitchen Mario Sarcletti Gisela Sturm Robert Zangerle

ORGANISATION Franz Allerberger (AGES GmbH) 137

Imprint: Published by: AGES - Austrian Agency for Health and Food Safety SpargelfeldstraĂ&#x;e 191, 1220 Vienna, Austria www.ages.at Graphic Design: strategy-design Photos: Michael Rathmayer ÂŠ AGES, May 2013

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