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Session 3: Methodological Insights on External Controls and Sensitivity Analyses
Session Chair(s)
John Concato, MD, MPH, MS
Associate Director for Real-World Evidence Analytics, OMP, CDER, FDA, United States
This session will highlight specific methodological issues relevant to real-world evidence. The first presentation will discuss results obtained when applying different methods to analyze data in externally controlled trials; the second presentation will discuss how external control arm data can help interpret results from single-arm trials; the third presentation will discuss a structured framework for sensitivity analyses to assess unmeasured confounding. A panel discussion will follow.
Learning Objective : At the conclusion of this session, participants should be able to:- Describe various statistical approaches for analyzing data in externally controlled trials
- Identify how external control arm data can be used to inform early decisions in drug development programs
- Recognize statistical methods used in sensitivity analyses to assess unmeasured confounding
Speaker(s)
Lisa Ensign, PHD, MSC
VP, Statistics and Regulatory Science Innovation, Medidata, a Dassault Systemes Company, United States
To Pursue or Not? How External Controls Were Used to Decide the Course of Two New Recurrent Glioblastoma Treatments
David Paulucci, MSC
Director, Data Science, BMS, United States
Deriving External Controls Arms From RWD: G-Computation and Digital Twins Applied to a Small Single Arm Phase 1 Trial
Mingyang Shan, PHD
Senior Director, Eli Lilly and Company, United States
Evaluating the Robustness of Real-World Evidence through Quantitative Sensitivity Analysis for Unmeasured Confounding
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