A signature enrichment design with Bayesian adaptive randomization

Abstract

Clinical trials in the era of precision cancer medicine aim to identify and validate biomarker signatures which can guide the assignment of individually optimal treatments to patients. In this article, we propose a group sequential randomized phase II design, which updates the biomarker signature as the trial goes on, utilizes enrichment strategies for patient selection, and uses Bayesian response-adaptive randomization for treatment assignment. To evaluate the performance of the new design, in addition to the commonly considered criteria of Type I error and power, we propose four new criteria measuring the benefits and losses for individuals both inside and outside of the clinical trial. Compared with designs with equal randomization, the proposed design gives trial participants a better chance to receive their personalized optimal treatments and thus results in a higher response rate on the trial. This design increases the chance to discover a successful new drug by an adaptive enrichment strategy, i.e. identification and selective enrollment of a subset of patients who are sensitive to the experimental therapies. Simulation studies demonstrate these advantages of the proposed design. It is illustrated by an example based on an actual clinical trial in non-small-cell lung cancer.

Keywords:

• Adaptive design
• precision medicine
• biomarker
• Bayesian adaptive randomization
• classifier
• enrichment strategy

2010 Mathematics Subject Classification:

• 62P10

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the U.S. National Science Foundation under Grant Division of Mathematical Sciences (DMS) [grant number 1612965]; the National Cancer Institute of the National Institutes of Health [grant numbers U54CA096300, U01CA152958 and 5P50CA100632]. The research of Huang was partially supported by the Dr Mien-Chie Hung and Mrs Kinglan Hung Endowed Professorship.