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Dataset Information

Enrichment Bayesian design for randomized clinical trials using categorical biomarkers and a binary outcome.


ABSTRACT:

Background

Adaptive clinical trials have been increasingly commonly employed to select a potential target population for one trial without conducting trials separately. Such enrichment designs typically consist of two or three stages, where the first stage serves as a screening process for selecting a specific subpopulation.

Methods

We propose a Bayesian design for randomized clinical trials with a binary outcome that focuses on restricting the inclusion to a subset of patients who are likely to benefit the most from the treatment during trial accrual. Several Bayesian measures of efficacy and treatment-by-subset interactions were used to dictate the enrichment, either based on Gail and Simon's or Millen's criteria. A simulation study was used to assess the performance of ou

SUBMITTER: Vinnat V 

PROVIDER: S-EPMC8882316 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature