The PROTECT project An Innovative PublicPrivate Partnership for
The PROTECT project An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology Olaf Klungel, Pharm. D, Ph. D Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University
ACKNOWLEDGEMENTS • The research leading to these results was conducted as part of the PROTECT consortium (Pharmacoepidemiological Research on Outcomes of Therapeutics by a European Consor. Tium, 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 (FP 7/2007 -2013) and EFPIA companies’ in kind contribution. • The views expressed are those of the authors only. • PROTECT work in this presentation is work by WP 2 colleagues.
Contents • Background PROTECT - Work package 2 (WP 2) • WP 2 working groups (WG) – Approach – Preliminary results (WG 1) – Results (WG 2 and WG 3) – Next steps • Conclusion 3
PROTECT Goal 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 These methods will be tested in real-life situations. 4
Data collection from consumers – WP 4 Clinical trials Observational studies Benefits Electronic health records Spontaneous ADR reports Risks Signal detection WP 3 Benefit-risk integration and representation – WP 5 Signal evaluation WP 2 Validation studies WP 6 Training and education WP 7 5
Partners Public Private Regulators: EFPIA companies: EMA (Co-ordinator) GSK (Deputy Coordinator) DKMA (DK) AEMPS (ES) MHRA (UK) Sanofi- Aventis Roche Novartis Academic Institutions: University of Munich Pfizer FICF (Barcelona) Genzyme Amgen INSERM (Paris) Mario Negri Institute (Milan) Poznan University of Medical Sciences Others: WHO UMC GPRD University of Groningen University of Utrecht Imperial College London University of Newcastle IAPO CEIFE Merck Serono Bayer Astra Zeneca Lundbeck Novo. Nordisk Takeda SMEs: Outcome Europe PGRx 6
WP 2: Framework for pharmacoepidemiological studies Objectives: To: • develop • test • disseminate methodological standards for the: • design • conduct • analysis of pharmacoepidemiological studies applicable to: • different safety issues • using different data sources 7
WP 2 participants and their role • WP 2 has 3 Working groups (WG) WG 1 Databases WG 2 Confounding WG 3 Drug utilization Number of participants n=46 33 public, 13 private n=14 10 public, 4 private n=9 5 public, 4 private Public partners EMA, LMU-Muenchen, AEMPS, CEIFE, GPRD, DKMA and UU UU FIFC, LMU Private partners Amgen, AZ, Genzyme, GSK, La-Ser, Merck, Novartis, Roche and Pfizer Amgen, Novartis and Roche WG Coordinators Raymond Schlienger 1 (Novartis) Mark de Groot 2 (UU) Nicolle Gatto (Pfizer) Rolf Groenwold (UU) Joan Fortuny 3 (Novartis) Luisa Ibanez (FIFC) WP 2 coleaders Olaf Klungel (UU) - Robert Reynolds (Pfizer) WP 2 coleaders alternates Tjeerd van Staa (GPRD) - Jamie Robinson (Roche) WP 2 Project Manager from Oct 2010 replacing John Weil (GSK) from 1 Feb. 2011 replacing Frank de Vries (UU) 3 from 15 March 2012 replacing Hans Petri (Roche) Ines Teixidor (UU) 1 2 8
Work Package 2 – WG 1: Databases Ü 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 • Danish National registries (DKMA) • British THIN databases (THIN) • Dutch Mondrian databases (MONDRIAAN) • Spanish BIFAP project (BIFAP) • British GPRD databases (GPRD) • German Bavarian claims database (BAVARIA) 9
Work Package 2 – WG 1: 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 10
Work Package 2 – WG 1: Databases Ü Selection of 5 key adverse events and drugs – Initial list of 55 events and >55 drugs – Finalisation based on literature review and consensus meeting Antidepressants (incl. Benzodiazepines) - Hip Fracture Antibiotics - Acute liver injury Beta 2 Agonists - Myocardial infarction Antiepileptics - Suicide Calcium Channel Blockers - Cancer 11
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) THIN UK GP 7. 8 M 3. 1 M Bavarian Claims DE Claims 10. 5 M 9. 5 M 12
Characteristics of 6 EU DBs Database Coding diagnoses Coding drugs Start year Nation wide GPRD Read BNF 2001 7% UK Mondrian ICPC ICD 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% UK Bavarian Claims ICD ATC 2001 84% (Bavaria) 13
Approach • Common protocol for each drug-ae pair – Descriptive studies for drug-ae pairs in all databases – 5 different study designs in selected databases – Extensive sensitivity analyses on main methodological issues • Common standards, templates, procedures – Detailed data specification including definitions of exposures, outcomes, and confounders for each database. – Blinding of results of individual DB analyses • Submission of protocols to ENCe. PP registry of studies 14
WG 1 Preliminary results: Antibiotic use by age in 6 EU databases DRAFT PRELIMINARY RESULTS 15
WG 1 Preliminary results: Antidepressant use by year in 6 EU databases DRAFT PRELIMINARY RESULTS 16
WG 1 Preliminary results: BZD use by age in 6 EU databases DRAFT PRELIMINARY RESULTS 5000 Prevalence per 10. 000 p-y 4500 BIFAP DENMARK 4000 GPRD 3500 MONDRIAAN-LINH MONDRIAAN-ZGA 3000 THIN 2500 2000 1500 1000 500 0 0 -9 10 -19 20 -29 30 -39 40 -49 50 -59 60 -69 70 -79 80 -89 90+ AGE GROUP Mondriaan-ZGA: results correspond to 2008 17
WG 1 Preliminary results: Incidence of hip/femur fracture by age in 2009 in 4 EU databases DRAFT PRELIMINARY RESULTS 18
Work Package 2 – WG 2: Confounding Work Plan • Objective – To evaluate and improve innovative methods to control confounding • Method – Simulation studies to test methods – Application of methods to real-life data sets 19
Work Package 2 – WG 2: Confounding Progress status • Guideline for conduct of simulation studies – Propensity score methods – Instrumental variable methods • First results – Usefulness of measures for balance for reporting of the amount of balance reached in PS analysis and selecting the final PS model – Comparison of methods to control for time-dependent confounding – Evaluation of IV in case-control and cohort studies 20
Simulation study propensity scores 21
Application of propensity scores 22
Work Package 2 – WG 2: Confounding Next steps • Analysis of instrumental variables (IV) in Drug AE pairs – Evaluate the potential for IV analysis on the selected Drug AE pairs in the databases that are available within PROTECT – Feb 2012: Identify potential IV for each of the 5 Drug AE pair and in each WG 1 database – Aug 2013: Results of IV studies in databases (if an appropriate IV can be identified & measured) 23
Work Package 2 – WG 3: Drug Utilisation Work Plan • Use of national drug utilisation data (incl IMS) • Inventory of data sources on drug utilisation data for several European countries • Evaluation and dissemination of methodologies for drug utilisation studies in order to estimate the potential public health impact of adverse drug reactions • Collaboration with Euro. DURG agreed 24
Work Package 2 – WG 3: Drug Utilisation Progress Status Ü Inventory on Drug Use data “Drug consumption databases in Europe” (last version August 2011: http: //www. imi-protect. eu/results. html) – 11 research working groups across Europe identified – Databases heterogeneous, administrative focus and influenced by the national health system structure • Collecting DU data (in/out hospital) – from public databases (for 6 selected drugs) – from IMS (Antibiotics, Antidepressants and Benzodiazepines. Explored for other drugs) 25
Work Package 2 – WG 3: Drug Utilisation Next steps • Literature Search on Randomized Controlled Trials (RCT) – Search for existing meta-analyses or syntheses available in the literature (avoid duplication of work already done). – Dec 2011: Development of specific protocols for literature search Jan 2012: Start of literature search starts. – Dec 2012: Results of the literature search on RCTs expected. • Public health impact of selected Drug AE pairs – Evaluate validity of drug use data – Estimate the exposed population to drugs and calculate population attributable risk 26
27
Finally • Reduce variation due to methodological choice of individual researchers • Explain variation due to characteristics of country/database • Disseminate methodological guidance for PE studies • More consistency in drug-ae studies to improve B/R assessment of medicines 28
Members of PROTECT WP 2 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 (Astra. Zeneca); 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 (Glaxo. Smith. Kline 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 KGa. A ); 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). 29
- Slides: 29