A Case Study of an Adaptive Clinical Trial in the Treatment of Out-Patients with Depressive Disorder

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Abstract
Adaptive clinical trials have attracted the attention of statisticians because they allow for information accrued early in the trial to influence the allocation of treatment of later enrolled patients, thus allowing those patients an increased likelihood of receiving the better treatment. Few adaptive clinical trials have been reported in the literature; the purpose of this article is to describe the rationale, design, and analysis of a recently completed adaptive trial. Simulations to address sample size issues are presented. A Bayesian and a frequentist randomization analysis are discussed. The randomization analysis addresses the use of an adaptive allocation scheme, a delayed response, and a surrogate response. In this trial, the differences between the Bayesian and randomization inference were small. Some suggestions for future implementation of adaptive clinical trials and future research areas are provided.

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