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群组序贯试验设计中所需样本量变化的考虑。

Accounting for variation in the required sample size in the design of group-sequential trials.

机构信息

Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK.

Centre for Trials Research, Cardiff University, Cardiff, UK.

出版信息

Contemp Clin Trials. 2021 Aug;107:106459. doi: 10.1016/j.cct.2021.106459. Epub 2021 May 31.

Abstract

INTRODUCTION

Most literature on optimal group-sequential designs focuses on minimising the expected sample size. We highlight other factors for consideration.

METHODS

We discuss several quantities less-often considered in adaptive design: the median and standard deviation of the random required sample size, and the probability of committing an interim error. We consider how the optimal timing of interim analyses changes when these quantities are accounted for.

RESULTS

Incorporating the standard deviation of the required sample size into an optimality framework, we demonstrate how and when this quantity means using a group-sequential approach is not optimal. The optimal timing of an interim analysis is shown to be highly dependent on the pre-specified preference for minimising the expected sample size relative to its standard deviation.

CONCLUSIONS

Examining multiple factors, which measure the advantages and disadvantages of group-sequential designs, helps determine the best design for a specific trial.

摘要

简介

大多数关于最优分组序贯设计的文献都集中在最小化预期样本量上。我们强调了其他需要考虑的因素。

方法

我们讨论了自适应设计中较少考虑的几个数量:随机所需样本量的中位数和标准差,以及发生中期错误的概率。我们考虑了当考虑这些数量时,中期分析的最佳时机如何变化。

结果

将所需样本量的标准差纳入优化框架,我们展示了当这种数量意味着使用分组序贯方法不是最优时,如何以及何时会出现这种情况。中期分析的最佳时机高度依赖于预先指定的偏好,即相对于其标准差最小化预期样本量。

结论

检查多个衡量分组序贯设计优缺点的因素有助于确定特定试验的最佳设计。

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