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临床试验中多个终点的一些统计方法。

Some statistical methods for multiple endpoints in clinical trials.

作者信息

Zhang J, Quan H, Ng J, Stepanavage M E

机构信息

Merck Research Laboratories, Clinical Biostatistics and Research Data Systems, Rahway, NJ 07065-0900, USA.

出版信息

Control Clin Trials. 1997 Jun;18(3):204-21. doi: 10.1016/s0197-2456(96)00129-8.

Abstract

This paper summarizes, defines, and discusses multiple endpoints comparison procedures, concepts, and methodologies for applications to clinical trials. We address the more widely used methods of alpha-level, p-value, and critical value adjustments. We examine global assessment measures such as O'Brien's test and Simes' procedure and contrast them with the alpha-adjustment procedures of Bonferroni and Holm. We propose a global assessment procedure based on categorization of the individual endpoints to form an overall composite endpoint. Additionally, we discuss a new weighting scheme for Holm's sequentially rejective alpha-adjustment procedure. Investigation of the correlation between endpoints is examined in relation to adjustment of the alpha-level. In the context of a clinical trial, the above multiplicity procedures are applied and compared. Finally, some comments concerning ease of use and relevance are summarized for the above methods.

摘要

本文总结、定义并讨论了多种用于临床试验的终点比较程序、概念和方法。我们阐述了更为广泛使用的α水平、p值和临界值调整方法。我们研究了诸如奥布赖恩检验和西姆斯程序等全局评估方法,并将它们与邦费罗尼和霍尔姆的α调整程序进行对比。我们提出了一种基于对各个终点进行分类以形成总体复合终点的全局评估程序。此外,我们讨论了霍尔姆序贯拒绝α调整程序的一种新的加权方案。结合α水平的调整,研究了终点之间的相关性。在一项临床试验的背景下,应用并比较了上述多重性程序。最后,总结了关于上述方法易用性和相关性的一些评论。

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