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Activity Number: 360 - Contributed Poster Presentations: Section on Bayesian Statistical Science
Type: Contributed
Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #309748
Title: Comparative Effectiveness Research Using Bayesian Adaptive Designs for Rare Diseases: Response Adaptive Randomization Reusing Participants
Author(s): Fengming Tang* and Byron J Gajewski
Companies: KUMC and KUMC
Keywords: Comparative Effectiveness Research; Bayesian Adaptive Model; hierarchical models; response adaptive randomization
Abstract:

Slow accrual rate is a major challenge in clinical trials for rare diseases. This challenge is amplified in comparative effectiveness research where multiple treatments are compared. Novel efficient clinical trial designs are in urgent need in these areas. Our proposed response adaptive randomization (RAR) reusing participants trial design mimics the real world clinic practice that allows patients to switch treatments when desired outcome is not achieved. Two strategies were used to increase efficiency: 1) Allowing participants to switch treatments so that each participant can have more than one observation and hence controlling for participant specific variability is possible; and 2) Utilizing RAR, which has been broadly accepted to be efficient, to allocate more participants to the promising arms. Extensive simulations were conducted and showed that, compared with conventional RAR, where each participant is randomized to one treatment, the proposed participants reusing RAR design can achieve comparable power with a much smaller sample size and a much shorter trial duration when accrual rate is low. The efficiency gain decreases as accrual rate increases.


Authors who are presenting talks have a * after their name.

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