Suppr超能文献

加权参数群组序贯设计的统一框架。

A unified framework for weighted parametric group sequential design.

机构信息

Merck & Co., Inc., Rahway, NJ, USA.

出版信息

Biom J. 2022 Oct;64(7):1219-1239. doi: 10.1002/bimj.202100085. Epub 2022 Jun 15.

Abstract

Group sequential design (GSD) is widely used in clinical trials in which correlated tests of multiple hypotheses are used. Multiple primary objectives resulting in tests with known correlations include evaluating (1) multiple experimental treatment arms, (2) multiple populations, (3) the combination of multiple arms and multiple populations, or (4) any asymptotically multivariate normal tests. In this paper, we focus on the first three of these and extend the framework of the weighted parametric multiple test procedure from fixed designs with a single analysis per objective to a GSD setting where different objectives may be assessed at the same or different times, each in a group sequential fashion. Pragmatic methods for design and analysis of weighted parametric group sequential design under closed testing procedures are proposed to maintain the strong control of the family-wise Type I error rate when correlations between tests are incorporated. This results in the ability to relax testing bounds compared to designs not fully adjusting for known correlations, increasing power, or allowing decreased sample size. We illustrate the proposed methods using clinical trial examples and conduct a simulation study to evaluate the operating characteristics.

摘要

分组序贯设计(GSD)广泛应用于临床研究中,其中使用了多个相关的假设检验。具有已知相关性的多个主要目标包括评估(1)多个实验治疗组,(2)多个群体,(3)多个组和多个群体的组合,或(4)任何渐近多元正态检验。在本文中,我们专注于其中的前三个,并将加权参数多重检验程序的框架从每个目标只有一次分析的固定设计扩展到 GSD 设置,其中不同的目标可能在相同或不同的时间以分组序贯的方式进行评估。针对在封闭检验程序下加权参数分组序贯设计的设计和分析提出了实用的方法,以在纳入检验之间的相关性时保持对总体型 I 错误率的强有力控制。这使得与未完全调整已知相关性的设计相比,能够放宽检验界限,提高功效,或允许减少样本量。我们使用临床试验示例来说明所提出的方法,并进行模拟研究以评估其操作特性。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验