Bayesian Optimal Designs for Multi-Arm Multi-Stage Phase II Randomized Clinical Trials with Multiple Endpoints.

ABSTRACT: There is a growing need to evaluate of multiple competing drugs in phase II trials where the number of patients is often limited, and simultaneous assessment of both efficacy and toxicity is crucial. To avoid the waste of research resources, it is indeed more efficient to screen multiple drugs at once in a platform phase II setting. We aim to adapt the Bayesian optimal phase II (BOP2) design to multi-arm trials for both uncontrolled and controlled settings. The binary efficacy and toxicity endpoints are modeled by a Dirichlet distribution as a vector of four outcomes. Posterior marginal distributions at each analysis are used to derive the monitoring threshold that varies during the trial. We control the family-wise Type I error rate for multiple comparison against a common reference value

SUBMITTER: Mulier G 

PROVIDER: S-EPMC11412438 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature