Lessons Learned from PROTECT on Common Protocols for Multi-Database Studies
- Insights into common protocol studies – including a list of recommendations – which were conducted in the framework of the PROTECT project.
- Presented by: Olaf Klungel, Utrecht Universiteit
- Presented at: ENCePP Plenary Meeting, 24 November 2015
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 are being tested in real-world situations.
Main Objectives
- Explain differences in drug-adverse event associations due to choices in methodology and databases
- Replication program of studies
- Same study EU database
- Different study database, specifically US data source
(Abbing-Karahagopian V, et al. Curr Clin Pharmacol 2014;9:130-138)
Procedures
- Common protocol for each drug-AE pair
- 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 in-parallel and replication analyses
- Stepwise unblinding after completion of each design
- Registration of protocols at ENCePP to guarantee transparency
Challenges/ Lessons Learned
- Substantial time (+/-1 year) reach agreement on common protocol – Consensus/buy-in on approach between stakeholders!
- Research question determined choice of database and design of data collection
- Detailed data-specification documents are needed to harmonize procedures and analyses
- Frequent communication between research centres to reduce variation in “interpretation” of protocol
- During programming and analysis phase further clarification is required and needs documentation
Methodological Determinants of Drug-AE Associations
- Databases
- Study design
- Outcome definition
- Exposure definition
- Methods to control for confounding
Recommendations
- Develop common protocol with great detail to reduce methodological differences and “interpretation” by researchers
- Solid infrastructure fo rcommunication/collaboration
- Conduct analysis in parallel in multiple DBs versus “apriori” pooling of DBs
- Cherish heterogeneity and explore its sources
- To test robustness of findings conduct multiple sensitivity analyses:
- Multiple designs (e.g. Cohort/case-control vs case-only)
- Exposure (e.g. Individual AEDs), outcome (e.g SUI), confounding adjustment
- Replication needed if parallel analysis consistent?
What’s Next?
- Network for observational safety and effectiveness studies
- Common protocol in multiple databases may increase confidence in investigations
- Testing of existing network
- New safety signals
- Platform for methods development and testing
- Further development of network infrastructure • Library of codes/programs
- Governance of network
- Structure for collaboration/communication
- Collaboration with other networks