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Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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Page 1: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Explaining differences in drug-adverse event associations across and within EU databases

The PROTECT project

Olaf Klungel, PharmD, PhD

Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University

An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

Page 2: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

ACKNOWLEDGEMENTS

• The research leading to these results was conducted as part of the PROTECT consortium (Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium, www.imi-protect.eu) which is a public-private partnership coordinated by the European Medicines Agency.

• The PROTECT project has received support from the Innovative Medicine Initiative Joint Undertaking (www.imi.europa.eu) under Grant Agreement n° 115004, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.

• The views expressed are those of the authors only.• PROTECT work in this presentation is work by WP2 colleagues.

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Page 3: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Contents

• Background PROTECT (WP2)• Selection of 6 drug-ae pairs• Analysis in 6 EU databases• Preliminary descriptive results • Population impact across EU countries• Conclusion

Page 4: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

PROTECT Goal

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These methods will be tested in real-life situations.

To strengthen the monitoring of benefit-risk of medicines in Europe by developing

innovative methods

to enhance early detection and assessment of adverse drug reactions from different data

sources (clinical trials, spontaneous reporting and

observational studies)

to enable the integration and presentation of data

on benefits and risks

Page 5: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Partners

5

Public PrivateRegulators:

EMA (Co-ordinator)

DKMA (DK)

AEMPS (ES)

MHRA (UK)

Academic Institutions:

University of Munich

FICF (Barcelona)

INSERM (Paris)

Mario Negri Institute (Milan)

Poznan University of Medical Sciences

University of Groningen

University of Utrecht

Imperial College London

University of Newcastle

EFPIA companies:GSK (Deputy Co-ordinator)

Sanofi- Aventis

Roche

Novartis

Pfizer

Amgen

Genzyme

Merck Serono

Bayer

Astra Zeneca

Lundbeck

NovoNordisk

Takeda

SMEs:

Outcome Europe

PGRx

Others:

WHO UMC

GPRD

IAPO

CEIFE

Page 6: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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WP2 participants and their role

• WP2 has 3 Working groups (WG)

WG1Databases

WG2Confounding

WG3Drug utilization

Number of participants

n=4633 public, 13 private

n=1410 public, 4 private

n=95 public, 4 private

Public partners EMA, LMU-Muenchen, AEMPS, CEIFE, GPRD, DKMA and UU UU FIFC

Private partners Amgen, AZ, Genzyme, GSK, La-Ser, Merck, Novartis, Roche and Pfizer Amgen, Novartis, Roche and Pfizer Amgen, Novartis and Roche

WG Coordinators Raymond Schlienger 1 (Novartis)Mark de Groot2 (UU)

Nicolle Gatto (Pfizer)Rolf Groenwold (UU)

Joan Fortuny 3 (Novartis)Luisa Ibanez (FIFC)

WP2 coleaders Olaf Klungel (UU) - Robert Reynolds (Pfizer)

WP2 coleaders alternates

Tjeerd van Staa (GPRD) - Jamie Robinson (Roche)

WP2 Project Manager Ines Teixidor (UU)

1 from Oct 2010 replacing John Weil (GSK)2 from 1 Feb. 2011 replacing Frank de Vries (UU)3 from 15 March 2012 replacing Hans Petri (Roche)

Page 7: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

WP 2: Framework for pharmacoepidemiological studies

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To:• develop• test• disseminate

of pharmacoepidemiological studies applicable to:• different safety issues• using different data sources

methodological standards for the:• design• conduct• analysis

Objectives:

Page 8: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Two studies on the use of statins and the risk of fracture done in GPRD around the same period by two different groups.

Meier et al., 2000 Van Staa et al., 2011

Statins only Current use 0.55 (0.44-0.69) Current use 1.01 (0.88-1.16)

N prescriptions Time since use

• 1-4• 5-19• 20

0.51 (0.33-0.81)0.62 (0.45-0.85)0.52 (0.36-0.76)

• 0-3 months• 3-6 months• 6-12 months• > 12 months

0.71 (0.50-1.01)1.31 (0.87-1.95)1.14 (0.82-1.58)1.17 (0.99-1.40)

Recent use 0.67 (0.50-0.92)

Past use 0.87 (0.65-1.18) Past use 1.01 (0.78-1.32)

Statins (current) and type of fractures

FemurHand, wrist or armVertebralOther

0.12 (0.04-0.41)0.71 (0.52-0.96)0.14 (0.02-0.88)0.43 (0.23-0.80)

HipRadius/ulnaVertebral

0.59 (0.31-1.13)1.01 (0.80-1.27)1.15 (0.62-2.14)

Page 9: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Why such a difference ?

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Meier et al., 2000 Van Staa et al., 2011

Source population370 GPRD practices 683 GPRD practices

Study period Through Sept 1998 Through July 1999

Design Selected case control (3 cohorts) Conventional case-control

N Cases 3,940 81,880

N Controls 23,379 81,880

Age 50-6970-7980-89

52.2%28.9%18.9%

50-6970-84>85

47.9%38.9%13.2%

Sex Female 75.0% Female 75.6%

BMI ≥ 25 57.3% ≥ 25 52.3%

• Different patients (source population, study period, exclusion criteria)

• Study design (e.g. matching criteria for age)

• Definition of current statin use (last 6 months vs. last 30 days)

• Possibly different outcomes (mapping)

• Possibly uncontrolled/residual confounding

Page 10: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Work Package 2 – WG1: Databases

Conduct of adverse event - drug pair studies in different EU databases• Selection of 5 key adverse event - drug pairs• Development of study protocols for all pairs• Compare results of studies • Identify sources of discrepancies

Databases

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• British THIN databases• Spanish BIFAP project• German Bavarian claims database

• Danish National registries• Dutch Mondrian databases• British GPRD databases

Page 11: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Work Package 2 – WG1: Databases

Selection of key adverse events and drugs• Selection criteria:– Adverse events that caused regulatory decisions– Public health impact (seriousness of the event,

prevalence of drug exposure, etiologic fraction)– Feasibility– Range of relevant methodological issues

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Page 12: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Work Package 2 – WG1: Databases

Antidepressants (incl. Benzodiazepines) - Hip Fracture

Antibiotics - Acute liver injury

Beta2 Agonists - Myocardial infarction

Antiepileptics - Suicide

Calcium Channel Blockers - Cancer

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Selection of 5 key adverse events and drugs– Initial list of 55 events and >55 drugs– Finalisation based on literature review and consensus

meeting

Page 13: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Population nr’s 6 EU databases

Database Country Source Cum Population nr Active population nr(2008)

GPRD UK GP 11 M 3.6 M

Mondrian NL Multisource 1.4 M (GP) 1 M (GP), 13.5 (Pharmacy), 1.2 M (Claims)

Bifap ES GP 3.2 M 1.6 M

Danish registries DK Multisource 5.2 M (All DBs) 5.2 M (All DBs)

THIN UK GP 7.8 M 3.1 M

Bavarian Claims DE Claims 10.5 M 9.5 M

Page 14: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Characteristics of 6 EU DBs

Database Coding diagnoses

Coding drugs

Start year Nation wide

GPRD Read BNF 2001 7% UK

Mondrian ICPCICD

ATC 1991 90% NL (pharmacy)0.6% NL (GP)

Bifap ICPC ATC 2001 7% ES

Danish registries ICD ATC 1994 (med prod)1977 (pat register)

100% DK

THIN READ BNF 2003 5.7% UKBavarian Claims ICD ATC 2001 84% (Bavaria)

Page 15: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Approach

• Common protocol for each drug-ae pair– Extensive sensitivity analyses on main

methodological issues• Leader(s) for each protocol• Leader(s) for each database• Detailed data specification including definitions

of exposures, outcomes, and confounders for each database.

• Blinding of results of individual DB analyses

Page 16: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Preliminary results: Antibiotic use by year in 6 EU databases

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DRAFT PRELIMINARY RESULTS

Page 17: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Preliminary results: Antibiotic use by age in 6 EU databases

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DRAFT PRELIMINARY RESULTS

Page 18: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Preliminary results: Antibiotic use in 4 EU databases

• Point prevalence of Antibiotic Exposure by season from 2004-2009

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DRAFT PRELIMINARY RESULTS

Page 19: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Preliminary results: Antidepressant use by year in 6 EU databases

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DRAFT PRELIMINARY RESULTS

Page 20: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

Preliminary results: BZD use per year for 6 EU databases

2001 2002 2003 2004 2005 2006 2007 2008 20090

200

400

600

800

1000

1200

1400

1600

1800

BIFAP DENMARK GPRDMONDRIAAN/LINH MONDRIAAN/ZGA THIN

Years

Pre

vale

nce p

er

10.0

00 p

ers

on-y

ears

20

DRAFT PRELIMINARY RESULTS

Page 21: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Preliminary results: BZD use by age in 6 EU databases

0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80-89 90+0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

BIFAP

DENMARK

GPRD

MONDRIAAN-LINH

MONDRIAAN-ZGA

THIN

AGE GROUP

Pre

vale

nce

per

10.0

00 p

-y

Mondriaan-ZGA: results correspond to 2008

DRAFT PRELIMINARY RESULTS

Page 22: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Preliminary results: Incidence of hip/femur fracture in 6 EU databases

DRAFT PRELIMINARY RESULTS

Page 23: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Preliminary results: Incidence of hip/femur fracture by age in 2009 in 4 EU databases

DRAFT PRELIMINARY RESULTS

Page 24: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Page 25: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Page 26: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Page 27: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Page 28: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Page 29: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Calculation of Population Attributable Risk

Page 30: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Page 31: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Next steps

• Conduct of association studies 6 drug-ae pairs:

– Cohort studies (end 2012 complete)

– Nested case-control studies

– Population-based control studies

– Case-cross over studies

– Self-controlled case series

Page 32: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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• Reduce variation due to methodological choice of individual

researchers

• Explain variation due to characteristics of country/database

• More consistency in drug-ae studies to improve B/R assessment

of medicines

Finally

Page 33: Explaining differences in drug-adverse event associations across and within EU databases The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology

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Members of PROTECT WP2

J. Slattery, Y. Alvarez, G. Candore, J. Durand (European Medicines Agency); J. Hasford, M. Rottenkolber (Ludwig-Maximilians-Universität-München); S. Schmiedl (Witten University); F. de Abajo Iglesias, A. Afonso, M. Gil, C. Huerta Alvarez, B. Oliva, G. Requena (Agencia Espanola de Medicamentos y Productos Sanitarios); R. Brauer, G. Downey, M. Feudjo-Tepie, M. Schoonen (Amgen NV); S. Johansson (AstraZeneca); J. Robinson, M. Schuerch, I. Tatt (Roche); L.A. Garcia, A. Ruigomez (Fundación Centro Español de Investigación Farmacoepidemiológica); J. Campbell, A. Gallagher, E. Ng, T. Van Staa (General Practice Research Database); O. Demol (Genzyme); J. Logie, J. Pimenta, K. Davis (GlaxoSmithKline Research and Development LTD); L. Bensouda-Grimaldi (L.A. Sante Epidemiologie Evaluation Recherche); U. Hesse, P. F. Rønn (Lægemiddelstyrelsen (Danish Medicines Agency) ); M. Miret (Merck KGaA ); P. Primatesta, R. Schlienger, E. Rivero, J. Fortuny (Novartis); A. Bate, N. Gatto, R. Reynolds (Pfizer); E. Ballarin, L. Ibañez, J.R. Laporte, M. Sabaté, P. Ferrer (Fundació Institut Català de Farmacologia); V. Abbing-Karahagopian, D. de Bakker, M.L. de Bruin, F. de Vries, A.C.G. Egberts, B. Leufkens, P. Souverein, L. van Dijk, E. Voogd, M. De Groot, H. Gardarsdottir, F. Rutten, R. Van den Ham, O. Klungel, S. Belitser, A. De Boer, R. Groenwold, A. Hoes, W. Pestman, K. Roes, S. Ali, J. Uddin (Universiteit Utrecht).