A Design for Testing Clinical Strategies: Biased Adaptive Within-Subject Randomization

Summary We propose a method for assigning treatment in clinical trials, called the ‘biased coin adaptive within-subject’ (BCAWS) design: during the course of follow-up, the subject’s response to a treatment is used to influence the future treatment, through a ‘biased coin’ algorithm. This design results in treatment patterns that are closer to actual clinical practice and may be more acceptable to patients with chronic disease than the usual fixed trial regimens, which often suffer from drop-out and non-adherence. In this work, we show how to use the BCAWS design to compare treatment strategies, and we provide a simple example to illustrate the method.