Process guide for inferential studies using healthcare data from routine clinical practice to evaluate causal effects of drugs (PRINCIPLED): considerations from the FDA Sentinel Innovation Center

This report proposes a stepwise process covering the range of considerations to systematically consider key choices for study design and data analysis for non-interventional studies with the central objective of fostering generation of reliable and reproducible evidence. These steps include (1) form...

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Bibliographic Details
Published in:BMJ (Online) 2024-02, Vol.384, p.e076460-e076460
Main Authors: Desai, Rishi J, Wang, Shirley V, Sreedhara, Sushama Kattinakere, Zabotka, Luke, Khosrow-Khavar, Farzin, Nelson, Jennifer C, Shi, Xu, Toh, Sengwee, Wyss, Richard, Patorno, Elisabetta, Dutcher, Sarah, Li, Jie, Lee, Hana, Ball, Robert, Dal Pan, Gerald, Segal, Jodi B, Suissa, Samy, Rothman, Kenneth J, Greenland, Sander, Hernán, Miguel A, Heagerty, Patrick J, Schneeweiss, Sebastian
Format: Article
Language:English
Subjects:
Clinical medicine
Diabetes
Drugs
Electronic health records
Glucose
Health care policy
Health insurance
Hemoglobin
Infections
Insurance claims
Observational studies
Research Methods & Reporting
Sensitivity analysis
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Summary:This report proposes a stepwise process covering the range of considerations to systematically consider key choices for study design and data analysis for non-interventional studies with the central objective of fostering generation of reliable and reproducible evidence. These steps include (1) formulating a well defined causal question via specification of the target trial protocol; (2) describing the emulation of each component of the target trial protocol and identifying fit-for-purpose data; (3) assessing expected precision and conducting diagnostic evaluations; (4) developing a plan for robustness assessments including deterministic sensitivity analyses, quantitative bias analyses, and net bias evaluation; and (5) inferential analyses.
ISSN:1756-1833
1756-1833
DOI:10.1136/bmj-2023-076460