BSWG KOL Lecture Series, L17

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Speaker: Rajat Mukherjee, PhD (Cytel)

Title: A Bayesian Sequential Design for COVID-19 Vaccine Trials

Abstract: We present a Bayesian design for studying the efficacy of BCG and a competitor TB vaccine in preventing symptomatic COVID-19 infections in health care workers. The proposed design offers flexibility of sample size by having regular interim looks. At each interim look, the predictive power with the current cohort is computed and decision to stop enrollment or continue to the next interim is made based on the predictive power reaching a certain pre-specified threshold. Once the predictive power crosses this threshold, the study enter a close-out phase and the final analysis is conducted once all recruited subjects have completed the minimal follow-up time. The design can also allow for dropping a non-efficacious arm and for futility stopping. Design parameters are all pre-specified and determined via evaluation of the frequentist operating characteristics based on simulations.

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