A Bayesian adaptive design for biomarker trials with linked treatments.

ABSTRACT:

Background

Response to treatments is highly heterogeneous in cancer. Increased availability of biomarkers and targeted treatments has led to the need for trial designs that efficiently test new treatments in biomarker-stratified patient subgroups.

Methods

We propose a novel Bayesian adaptive randomisation (BAR) design for use in multi-arm phase II trials where biomarkers exist that are potentially predictive of a linked treatment's effect. The design is motivated in part by two phase II trials that are currently in development. The design starts by randomising patients to the control treatment or to experimental treatments that the biomarker profile suggests should be active. At interim analyses, data from treated patients are used to update the allocation probabilities. If

SUBMITTER: Wason JM 

PROVIDER: S-EPMC4559835 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature