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Activity Number: 145 - Leveraging External Data in Clinical Trials
Type: Contributed
Date/Time: Monday, August 8, 2022 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #322926
Title: Evaluating Propensity-Score Augmentation of Real-World Controls in Clinical Studies
Author(s): Mingyang Shan* and Yang Ou and Tongrong Wang and Ilya Lipkovich and Douglas Faries
Companies: Eli Lilly and Company and University of Pittsburgh and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly & Company
Keywords: RCT; external control arm; real world control arm; hybrid control arm; propensity score
Abstract:

There has been an increasing interest in improving the efficiency of clinical studies by leveraging real-world data (RWD). FDA guidance suggests that external data sources should be selected with careful considerations on the appropriateness of the study population, exposures, outcomes, and key covariates. Bayesian and frequentist integrated propensity score methods have been proposed to dynamically augment RCTs with subjects from RWD and have been shown to be superior to traditional methods under potential selection bias. However, causal inference using multiple data sources requires unconfoundedness of the treatment assignment mechanism and strong ignorability of the data source (exchangeability of the distributions of potential outcomes across studies). A simulation study is presented to evaluate the operating characteristics of integrated propensity score methods under violations of the unconfoundedness and strong data source ignorability assumptions.


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