基于分组顺序设计中条件功率的贝塔支出函数

IF 1.3 3区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Biometrical Journal Pub Date : 2024-04-05 DOI:10.1002/bimj.202300094
Senmiao Ni, Zihang Zhong, Zhiwei Jiang, Yang Zhao, Jingwei Wu, Hao Yu, Jianling Bai
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引用次数: 0

摘要

条件幂(CP)是一种在分组序列设计中广泛使用的无效监测方法。然而,采用 CP 方法可能会导致无法将 II 型误差率控制在理想水平。在本研究中,我们引入了一种灵活的贝塔支出函数(CP-beta 支出函数),该函数根据预定的标准化效应大小,在采用 CP 进行无效性监测的同时调节 II 型误差率。该函数划定了整个试验过程中 II 型误差率的支出。与其他现有的贝塔支出函数不同,CP-贝塔支出函数将贝塔支出概念无缝融入 CP 框架,有助于在无效性监测过程中精确控制 II 型误差率。此外,CP-贝塔支出函数衍生出的停止边界可以通过与其他传统贝塔支出函数方法类似的积分来计算。此外,所提出的 CP-beta 支出函数还能在试验的不同阶段适应 CP 尺度上的各种阈值,确保其在不同信息时间情景下的适应性。这些特性使 CP-贝塔支出函数在其他形式的贝塔支出函数中具有竞争力,使其适用于任何分组顺序设计的试验,并可直接实施。一项模拟研究和一个急性缺血性中风试验的例子都表明,即使在最初确定的样本量没有考虑无效停止的情况下,所提出的方法也能准确地捕捉到预期功率,并在保持明显无效的总体 I 类错误率方面表现出良好的性能。
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Beta spending function based on conditional power in group sequential design

Conditional power (CP) serves as a widely utilized approach for futility monitoring in group sequential designs. However, adopting the CP methods may lead to inadequate control of the type II error rate at the desired level. In this study, we introduce a flexible beta spending function tailored to regulate the type II error rate while employing CP based on a predetermined standardized effect size for futility monitoring (a so-called CP-beta spending function). This function delineates the expenditure of type II error rate across the entirety of the trial. Unlike other existing beta spending functions, the CP-beta spending function seamlessly incorporates beta spending concept into the CP framework, facilitating precise stagewise control of the type II error rate during futility monitoring. In addition, the stopping boundaries derived from the CP-beta spending function can be calculated via integration akin to other traditional beta spending function methods. Furthermore, the proposed CP-beta spending function accommodates various thresholds on the CP-scale at different stages of the trial, ensuring its adaptability across different information time scenarios. These attributes render the CP-beta spending function competitive among other forms of beta spending functions, making it applicable to any trials in group sequential designs with straightforward implementation. Both simulation study and example from an acute ischemic stroke trial demonstrate that the proposed method accurately captures expected power, even when the initially determined sample size does not consider futility stopping, and exhibits a good performance in maintaining overall type I error rates for evident futility.

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来源期刊
Biometrical Journal
Biometrical Journal 生物-数学与计算生物学
CiteScore
3.20
自引率
5.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.
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