Adaptive two-stage optimal designs for phase II clinical studies that allow early futility stopping
Adaptive two-stage optimal designs for phase II clinical studies that allow early futility stopping
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DOI：
10.1080/07474946.2019.1611307
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发表时间：
2019-04-03
影响因子：
0.8
通讯作者：
Jiang, Tao
中科院分区：
文献类型：
--
作者：
Shan, Guogen;Zhang, Hua;Jiang, Tao
适应性设计在当代临床试验中发挥着重要作用，使设计灵活高效。在癌症临床试验中，由于样本量相对较小，在这一阶段获得尽可能多的信息是很重要的。我们提出了一种新的自适应优化设计，即西蒙的两阶段设计，它只在第一阶段停止无效。由于计算优势，现有的自适应两阶段设计常常因无效或有效性而被允许停止。使用高效的搜索算法很难搜索到只在第一阶段失效的最优设计；例如，分支定界算法。我们必须使用多种计算技术来寻找最优设计。所提出的自适应设计满足单调性的重要性质，即第二阶段样本量是第一阶段响应数的非递增函数。在本文中，我们证明了所提出的自适应设计总是比Simon的最优设计具有更小的期望样本量。我们建议在实践中使用它作为常用的Simon设计的替代方案。
Adaptive designs play an important role in contemporary clinical trials to make designs flexible and efficient. In cancer clinical trials, given a relatively small sample size, it is important to obtain as much information as possible during this phase. We propose a new adaptive optimal design that stops for futility only in the first stage as Simon's two-stage design. The existing adaptive two-stage designs are often allowed to be stopped for futility or efficacy due to computational advantage. It is difficult to search for an optimal design with futility stopping only in the first stage by using efficient search algorithms; for example, the branch-and-bound algorithm. We have to use multiple computational techniques to search for the optimal design. The proposed adaptive design meets the important property of the monotonic property that the second stage sample size is a nonincreasing function of the number of responses from the first stage. In this article, we show that the proposed adaptive design always has a smaller expected sample size than Simon's optimal design. We recommend it for use in practice as an alternative to the commonly used Simon's design.