Novel methodologic approaches to phase I, II, and III trials.
Novel methodologic approaches to phase I, II, and III trials.
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DOI：
10.1161/strokeaha.111.000031
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发表时间：
2013-06
期刊：
影响因子：
8.3
通讯作者：
Yeatts SD
中科院分区：
文献类型：
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作者：
Yeatts SD
Yeatts Novel Trial Designs S117在K种干预措施（或K种干预措施和一种对照措施）中选择最佳措施进行进一步测试。在选择设计中，受试者将被随机分配至K种干预措施之一。最佳干预措施的定义是在数字上而不是在统计上具有最高答复率的干预措施。确定样本量以确保如果最佳治疗上级至少某个裕度D，则将以高概率选择最佳治疗。选择设计可以与序贯2阶段设计中的无效性或优效性检验相结合，如ALS（肌萎缩侧索硬化症）中Co-Q10试验所述。[10]在第1阶段结束时，将选择一种治疗方法，并在第2阶段结束时检验统计假设。在统计假设检验中纳入第1阶段受试者具有使用所有可用结局数据的优势，但会引入偏倚，这必须在检验统计量中考虑。如果第1阶段的受试者被排除在第2阶段的假设检验之外，参数估计是无偏的，但总的样本量增加了，自适应设计承诺增加试验的灵活性，以应对不断积累的信息，这一承诺既产生了热情，也产生了困惑。根据美国食品药品监督管理局的指南草案11，适应性设计“包括.重要的是要强调，潜在的问题，以及试验将以何种方式适应每个问题，必须在设计阶段预先规定，以保持试验的有效性。虽然肯定不是新的，但根据这一定义，组序贯方法是适应性的，因为它们允许在面临压倒性疗效或无效时，基于积累的数据提前停止试验。III期试验中其他有效的适应机制包括盲态样本量重新估计12和协变量自适应随机化。13基于对中期数据的非盲评估的调整，包括样本量重新估计和响应自适应随机化，可能更有吸引力，但在验证性环境中也可能更具争议。早期设计允许更灵活的适应，适应性设计在这种探索性环境中获得了更大的认可。无论是探索性还是验证性，贝叶斯还是频率论，每个试验都必须证明，面对所选择的适应，统计操作特征仍然是合理的。
Yeatts Novel Trial Designs S117 select the best among K interventions (or K interventions and a control) for further testing. In the selection design, subjects would be randomized to one of the K interventions. The best intervention is defined as the intervention with the numerically, rather than statistically, highest response rate. The sample size is determined to ensure that, if the best treatment is superior by at least some margin D, then the best treatment will be selected with high probability. The selection design can be combined with a futility or superiority test in a sequential 2-stage design, as described in the trial of Co-Q10 in ALS (amyotrophic lateral sclerosis). 10 At the conclusion of stage 1, a treatment would be selected, and the statistical hypothesis tested at the end of stage 2. Inclusion of stage 1 subjects in the statistical hypothesis test has the advantage of using all available outcome data but introduces bias, which must be accounted for in the test statistic. If the stage 1 subjects are excluded from the stage 2 hypothesis test, the parameter estimate is unbiased, but the overall sample size is increased.Adaptive designs promise increased flexibility of the trial to respond to accumulating information, a promise which has generated both enthusiasm and confusion. According to the Food and Drug Administration draft guidance, 11 an adaptive design “includes… a prospectively planned opportunity for modification of one or more specified aspects of the study design and hypotheses based on analysis of data (usually interim data) from subjects in the study.” It is important to emphasize that the potential issues, and in what manner the trial will adapt to each, must be prespecified in the design stage to maintain trial validity. Although certainly not novel, group sequential methods are adaptive according to this definition, in that they allow the trial to be stopped early, based on accumulating data, in the face of overwhelming efficacy or futility. Other valid mechanisms for adaptation in phase III trials include blinded sample size re-estimation12 and covariate adaptive randomization. 13 Adaptations based on an unblinded assessment of interim data, including sample size re-estimation and response adaptive randomization, may be more enticing but may also be more controversial in the confirmatory setting. Early phase designs allow for more flexibility with regard to adaptation, and adaptive designs have gained greater acceptance in this exploratory setting. Whether exploratory or confirmatory, Bayesian or Frequentist, each trial must demonstrate that the statistical operating characteristics remain sound in the face of the chosen adaptation (s).