Robertson D S, Wason J M S
MRC Biostatistics Unit, University of Cambridge, IPH Forvie Site, Robinson Way, Cambridge, CB2 0SR, UK.
Institute of Health and Society, Newcastle University, Newcastle upon Tyne, NE2 4AX, UK.
Biometrics. 2019 Sep;75(3):885-894. doi: 10.1111/biom.13042. Epub 2019 Apr 3.
Response-adaptive designs allow the randomization probabilities to change during the course of a trial based on cumulated response data so that a greater proportion of patients can be allocated to the better performing treatments. A major concern over the use of response-adaptive designs in practice, particularly from a regulatory viewpoint, is controlling the type I error rate. In particular, we show that the naïve z-test can have an inflated type I error rate even after applying a Bonferroni correction. Simulation studies have often been used to demonstrate error control but do not provide a guarantee. In this article, we present adaptive testing procedures for normally distributed outcomes that ensure strong familywise error control by iteratively applying the conditional invariance principle. Our approach can be used for fully sequential and block randomized trials and for a large class of adaptive randomization rules found in the literature. We show there is a high price to pay in terms of power to guarantee familywise error control for randomization schemes with extreme allocation probabilities. However, for proposed Bayesian adaptive randomization schemes in the literature, our adaptive tests maintain or increase the power of the trial compared to the z-test. We illustrate our method using a three-armed trial in primary hypercholesterolemia.
适应性设计允许随机化概率在试验过程中根据累积的反应数据进行变化，以便能将更大比例的患者分配到表现更好的治疗组中。在实际应用中，尤其是从监管角度来看，对适应性设计使用的一个主要担忧是控制I型错误率。具体而言，我们表明即使应用了邦费罗尼校正，简单的z检验仍可能具有过高的I型错误率。模拟研究常常被用于证明错误控制，但并不能提供保证。在本文中，我们针对正态分布的结果提出了适应性检验程序，通过迭代应用条件不变性原理确保严格的家族性错误控制。我们的方法可用于完全序贯和区组随机试验，以及文献中发现的一大类适应性随机化规则。我们表明，对于具有极端分配概率的随机化方案，要保证家族性错误控制在效能方面需付出高昂代价。然而，对于文献中提出的贝叶斯适应性随机化方案，与z检验相比，我们的适应性检验能保持或提高试验的效能。我们使用原发性高胆固醇血症的三臂试验来说明我们的方法。
