While randomization is the established method for obtaining scientifically valid treatment comparisons in clinical trials, it sometimes is at odds with what physicians feel is good medical practice. If a physician favors one treatment over another based on personal experience or published data, it may be more appropriate ethically for that physician to use the favored treatment, rather than enrolling patients on a randomized trial. Still, the randomized trial may later show the physician's favored treatment to be inferior. This paper reviews a statistical method, Bayesian adaptive randomization, that provides a practical compromise between the scientific ideal of conventional randomization and choosing each patient's treatment based on a personal preference that may prove to be incorrect. The method will first be illustrated by a simple hypothetical example, then by a recent trial in which patients with unresectable soft tissue sarcoma were adaptively randomized between two chemotherapy regimens.


Statistical Methodology | Statistical Theory