Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Biometry and Clinical Epidemiology, Charitéplatz 1, 10117 Berlin, Germany.
Institute of Medical Biometry and Informatics, University Medical Center Ruprechts-Karls University Heidelberg, Heidelberg, Germany.
Pharm Stat. 2021 Nov;20(6):1035-1050. doi: 10.1002/pst.2122. Epub 2021 Apr 1.
Sample size calculations in clinical trials need to be based on profound parameter assumptions. Wrong parameter choices may lead to too small or too high sample sizes and can have severe ethical and economical consequences. Adaptive group sequential study designs are one solution to deal with planning uncertainties. Here, the sample size can be updated during an ongoing trial based on the observed interim effect. However, the observed interim effect is a random variable and thus does not necessarily correspond to the true effect. One way of dealing with the uncertainty related to this random variable is to include resampling elements in the recalculation strategy. In this paper, we focus on clinical trials with a normally distributed endpoint. We consider resampling of the observed interim test statistic and apply this principle to several established sample size recalculation approaches. The resulting recalculation rules are smoother than the original ones and thus the variability in sample size is lower. In particular, we found that some resampling approaches mimic a group sequential design. In general, incorporating resampling of the interim test statistic in existing sample size recalculation rules results in a substantial performance improvement with respect to a recently published conditional performance score.
临床试验中的样本量计算需要基于深刻的参数假设。错误的参数选择可能导致样本量过小或过大，并可能产生严重的伦理和经济后果。适应性分组序贯研究设计是解决计划不确定性的一种方法。在这里，根据观察到的中期效果，可以在正在进行的试验中更新样本量。然而，观察到的中期效果是一个随机变量，因此不一定与真实效果相对应。处理与这个随机变量相关的不确定性的一种方法是在重新计算策略中包含重抽样元素。本文专注于具有正态分布终点的临床试验。我们考虑观察到的中期检验统计量的重抽样，并将这一原理应用于几种已建立的样本量重新计算方法。由此产生的重新计算规则比原始规则更平滑，因此样本量的变化更小。特别是，我们发现一些重抽样方法模拟了分组序贯设计。一般来说，在现有的样本量重新计算规则中纳入中期检验统计量的重抽样会导致与最近发布的条件性能得分相比，性能得到显著提高。
