Department of Statistics, Stanford University, Stanford, California 94305, USA.
Annu Rev Pharmacol Toxicol. 2012;52:101-10. doi: 10.1146/annurev-pharmtox-010611-134504. Epub 2011 Aug 11.
We review adaptive designs for clinical trials, giving special attention to the control of the Type I error in late-phase confirmatory trials, when the trial planner wishes to adjust the final sample size of the study in response to an unblinded analysis of interim estimates of treatment effects. We point out that there is considerable inefficiency in using the adaptive designs that employ conditional power calculations to reestimate the sample size and that maintain the Type I error by using certain weighted test statistics. Although these adaptive designs have little advantage over familiar group-sequential designs, our review also describes recent developments in adaptive designs that are both flexible and efficient. We also discuss the use of Bayesian designs, when the context of use demands control over operating characteristics (Type I and II errors) and correction of the bias of estimated treatment effects.
我们回顾了临床试验中的适应性设计，特别关注了在后期确证性试验中控制Ⅰ类错误的问题，此时试验设计者希望根据治疗效果的中期估计的非盲分析来调整研究的最终样本量。我们指出，使用适应性设计来重新估计样本量并通过使用某些加权检验统计量来维持Ⅰ类错误的方法存在很大的效率低下问题，这些适应性设计采用了条件功效计算。虽然这些适应性设计相对于熟悉的分组序贯设计没有什么优势，但我们的综述还描述了适应性设计的最新发展，这些设计既灵活又高效。我们还讨论了贝叶斯设计的使用，当使用环境需要控制操作特征（Ⅰ类和Ⅱ类错误）并纠正估计治疗效果的偏差时。
