Journal
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
Volume 61, Issue -, Pages 219-235Publisher
WILEY-BLACKWELL
DOI: 10.1111/j.1467-9876.2011.01006.x
Keywords
Adaptive randomization; Bayesian inference; Clinical trial ethics; Group sequential method; Posterior predictive distribution; Randomized trial; Type I error; Type II error
Categories
Funding
- Research Grants Council of Hong Kong
- US National Institutes of Health [CA16672, CA97007]
- M. D. Anderson University Cancer Foundation [80094548]
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We propose a randomized phase II clinical trial design based on Bayesian adaptive randomization and predictive probability monitoring. Adaptive randomization assigns more patients to a more efficacious treatment arm by comparing the posterior probabilities of efficacy between different arms. We continuously monitor the trial using the predictive probability. The trial is terminated early when it is shown that one treatment is overwhelmingly superior to others or that all the treatments are equivalent. We develop two methods to compute the predictive probability by considering the uncertainty of the sample size of the future data. We illustrate the proposed Bayesian adaptive randomization and predictive probability design using a phase II lung cancer clinical trial, and we conduct extensive simulation studies to examine the operating characteristics of the design. By coupling adaptive randomization and predictive probability approaches, the trial can treat more patients with a more efficacious treatment and allow for early stopping whenever sufficient information is obtained to conclude treatment superiority or equivalence. The design proposed also controls both the type I and the type II errors and offers an alternative Bayesian approach to the frequentist group sequential design.
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