A variational approach to optimal two-stage designs
A variational approach to optimal two-stage designs
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DOI：
10.1002/sim.8291
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发表时间：
2019-09-20
影响因子：
2
通讯作者：
Kieser, Meinhard
中科院分区：
文献类型：
--
作者：
Pilz, Maximilian;Kunzmann, Kevin;Kieser, Meinhard
在适应性两阶段设计中重新计算样本量是在临床试验中获得灵活性的公认方法。Jennison和Turnbull（2015）提出了一种基于逆正态组合检验的“最优”自适应两阶段设计，该设计在替代和条件功效下最小化期望样本量的混合准则。我们证明，使用组合测试是没有必要控制的第一类错误率，并使用变分技术开发一个通用的自适应设计，是全局最优的预定义的最优性标准。这种方法产生更有效的设计，并进一步允许调查的效率，逆正常的方法和局部（基于递归）重新计算规则和全局（无条件）自适应两阶段设计的最优性之间的关系。
Recalculating the sample size in adaptive two-stage designs is a well-established method to gain flexibility in a clinical trial. Jennison and Turnbull (2015) proposed an "optimal" adaptive two-stage design based on the inverse normal combination test, which minimizes a mixed criterion of expected sample size under the alternative and conditional power. We demonstrate that the use of a combination test is not necessary to control the type one error rate and use variational techniques to develop a general adaptive design that is globally optimal under predefined optimality criteria. This approach yields to more efficient designs and furthermore allows to investigate the efficiency of the inverse normal method and the relation between local (interim-based) recalculation rules and global (unconditional) optimality of adaptive two-stage designs.