The PROTECT project
An Innovative Public-Private Partnership for New Methodologies in
Pharmacovigilance and Pharmacoepidemiology
Olaf Klungel, PharmD, PhD
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 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.
Contents
• Background PROTECT - Work package 2 (WP2)
• WP2 working groups (WG)
– Approach
– Preliminary results (WG1)
– Results (WG2 and WG3)
– 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 – WP4
Clinical trials
Observational
studies
Benefits
Electronic
health records
Spontaneous
ADR reports
Risks
Signal detection
WP3
Benefit-risk integration and
representation – WP5
Signal evaluation
WP2
Validation
studies
WP6
Training and
education
WP7
5
Partners
Public
Private
Regulators:
EMA (Co-ordinator)
DKMA (DK)
EFPIA companies:
AEMPS (ES)
MHRA (UK)
Sanofi- Aventis
GSK (Deputy Coordinator)
Roche
Novartis
Academic Institutions:
University of Munich
FICF (Barcelona)
Pfizer
Amgen
Genzyme
INSERM (Paris)
Mario Negri Institute (Milan)
Poznan University of Medical
Sciences
University of Groningen
Others:
WHO UMC
GPRD
IAPO
University of Utrecht
Imperial College London
University of Newcastle
CEIFE
Merck Serono
Bayer
Astra Zeneca
Lundbeck
NovoNordisk
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
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WP2 participants and their role
•
WP2 has 3 Working groups (WG)
WG1
Databases
WG2
Confounding
WG3
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, 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
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
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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
• 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 – 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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Work Package 2 – WG1: Databases
 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
Beta2 Agonists - Myocardial infarction
Antiepileptics - Suicide
Calcium Channel Blockers - Cancer
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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
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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
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)
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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 ENCePP registry of studies
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WG1 Preliminary results:
Antibiotic use by age in 6 EU databases
DRAFT PRELIMINARY RESULTS
15
WG1 Preliminary results:
Antidepressant use by year in 6 EU databases
DRAFT PRELIMINARY RESULTS
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WG1 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
WG1 Preliminary results:
Incidence of hip/femur fracture by age in 2009 in 4 EU
databases
DRAFT PRELIMINARY RESULTS
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Work Package 2 – WG2: 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
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Work Package 2 – WG2: 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
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Simulation study propensity scores
21
Application of propensity scores
22
Work Package 2 – WG2: 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 WG1 database
– Aug 2013: Results of IV studies in databases (if an appropriate IV
can be identified & measured)
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Work Package 2 – WG3: 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 EuroDURG agreed
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Work Package 2 – WG3: Drug Utilisation
Progress Status
 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)
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Work Package 2 – WG3: 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
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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
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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).
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