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Activity Number: 295 - Adaptive Designs and Interim Analyses
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #322415 View Presentation
Title: A Practical Bayesian Adaptive Design with Application to Cardiovascular Outcomes Trials
Author(s): Matthew Psioda* and Joseph G Ibrahim and Mat Soukup
Companies: UNC Chapel Hill and UNC and Center for Drug Evaluation and Research, Office of Translational Sciences, FDA
Keywords: Clinical Trial Design ; Adaptive Design ; Bayesian ; Sample Size Determination ; Cardiovascular Outcomes Trial ; Simulation
Abstract:

Cardiovascular outcome trials (CVOTs) are commonly used to evaluate cardiovascular risk for new therapeutic agents intended for the treatment of Type 2 diabetes mellitus per FDA guidance. These trials are substantial in size and can take years to complete. To reduce their burden, we develop a Bayesian adaptive design which facilitates information borrowing from a historical CVOT using subject-level control data while assuring a reasonable upper bound on the maximum type I error rate and lower bound on the minimum power. First, one negotiates how much information may be borrowed from the historical CVOT, then constructs a data-based prior to be used for design and analysis of the new CVOT. At an interim analysis, one examines the degree of prior-data conflict. If there is too much conflict between the new CVOT data and the prior, the prior is discarded and the study proceeds to the final analysis where a non-informative prior is used. Otherwise, the CVOT is stopped early and the informative prior is used for analysis. We demonstrate our method by designing a new CVOT that borrows from the SAVOR trial, one of the first completed CVOTs.


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

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