Walter S D, Han H, Briel M, Guyatt G H
Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.
Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada.
Stat Med. 2017 Apr 30;36(9):1506-1518. doi: 10.1002/sim.7242. Epub 2017 Feb 9.
In this paper, we consider the potential bias in the estimated treatment effect obtained from clinical trials, the protocols of which include the possibility of interim analyses and an early termination of the study for reasons of futility. In particular, by considering the conditional power at an interim analysis, we derive analytic expressions for various parameters of interest: (i) the underestimation or overestimation of the treatment effect in studies that stop for futility; (ii) the impact of the interim analyses on the estimation of treatment effect in studies that are completed, i.e. that do not stop for futility; (iii) the overall estimation bias in the estimated treatment effect in a single study with such a stopping rule; and (iv) the probability of stopping at an interim analysis. We evaluate these general expressions numerically for typical trial scenarios. Results show that the parameters of interest depend on a number of factors, including the true underlying treatment effect, the difference that the trial is designed to detect, the study power, the number of planned interim analyses and what assumption is made about future data to be observed after an interim analysis. Because the probability of stopping early is small for many practical situations, the overall bias is often small, but a more serious issue is the potential for substantial underestimation of the treatment effect in studies that actually stop for futility. We also consider these ideas using data from an illustrative trial that did stop for futility at an interim analysis. Copyright © 2017 John Wiley & Sons, Ltd.
在本文中，我们考虑了从临床试验中获得的估计治疗效果中的潜在偏差，这些试验方案包括进行中期分析以及因无效性而提前终止研究的可能性。特别地，通过考虑中期分析时的条件把握度，我们推导出了各种感兴趣参数的解析表达式：(i) 在因无效性而停止的研究中治疗效果的低估或高估；(ii) 中期分析对已完成研究（即未因无效性而停止的研究）中治疗效果估计的影响；(iii) 具有此类停止规则的单个研究中估计治疗效果的总体估计偏差；以及(iv) 在中期分析时停止的概率。我们针对典型的试验场景对这些通用表达式进行了数值评估。结果表明，感兴趣的参数取决于许多因素，包括真实的潜在治疗效果、试验设计旨在检测的差异、研究把握度、计划的中期分析次数以及对中期分析后将要观察的未来数据所做的假设。由于在许多实际情况下提前停止的概率较小，总体偏差通常较小，但一个更严重的问题是，在实际因无效性而停止的研究中，治疗效果可能会被大幅低估。我们还使用了一个在中期分析时因无效性而停止的示例试验的数据来探讨这些观点。版权所有© 2017约翰·威利父子有限公司。
