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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

    Basic Details

    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.


    Rishi J Desai, Shirley V Wang, Sushama Kattinakere Sreedhara, Luke Zabotka, Farzin Khosrow-Khavar,  Jennifer C Nelson, Xu Shi, Sengwee Toh, Richard Wyss, Elisabetta Patorno, Sarah Dutcher, Jie Li, Hana Lee, Robert Ball, Gerald Dal Pan, Jodi B Segal, Samy Suissa, Kenneth J Rothman, Sander Greenland, Miguel A HernĂ¡n, Patrick J Heagerty, Sebastian Schneeweiss

    Corresponding Author

    Rishi J. Desai; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital; Harvard Medical School, Boston, MA