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Welcome and Opening Remarks and Keynote: Estimating Per-protocol Effects: Randomized Trials Analyzed like Observational Studies
Session Chair(s)
Brenda Crowe, PhD
Associate Vice President, Statistics
Eli Lilly and Company, United States
Fairouz Makhlouf, PhD
Deputy Director, Office of Biostatistics, Office of Translational Science, CDER
FDA, United States
The causal estimand of interest in many randomized trials is the intention-to-treat effect, that is, the effect of being assigned to the treatment strategies of interest. However, in many randomized trials, patients and doctors are more interested in another causal estimand: the per-protocol effect, that is, the effect of following the assigned treatment strategies as indicated in the protocol during the follow-up period. Valid estimation of the per-protocol effect generally requires adjustment for pre- and post-randomization prognostic factors associated with adherence and loss to follow-up. This talk describes the relative advantages and disadvantages of intention-to-treat and per-protocol effects, and reviews several case studies in cardiovascular disease, infectious disease, and cancer.
Speaker(s)
Keynote Presentation
Miguel Hernan, DrPH, MD
Department of Epidemiology, Harvard T.H. Chan School of Public Health, United States
Professor
Speaker
Representative Invited
FDA, United States
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