Suppr超能文献

生存分析导论:用于分析临床试验数据的统计方法

An introduction to survival analysis: statistical methods for analysis of clinical trial data.

作者信息

Greenhouse J B, Stangl D, Bromberg J

出版信息

J Consult Clin Psychol. 1989 Aug;57(4):536-44. doi: 10.1037//0022-006x.57.4.536.

Abstract

The randomized controlled clinical trial (RCT) is a prospective study using random assignment of subjects to treatment groups to compare the effect and value of a therapeutic intervention against a control. The RCT is the most definitive clinical research tool for evaluating the efficacy of a new therapy in human subjects. Often the outcome of interest in an RCT is the length of time until an event occurs after treatment or intervention. In this article we introduce statistical methods for evaluating differences in the patterns of time to response between two groups of subjects to determine whether one therapy is better than another. The collection of methods for analyzing such data, known as survival data, is called survival analysis. Using data from a hypothetical clinical trial for the prevention of the recurrence of depression, we illustrate two elementary methods for analyzing survival data. We also discuss generalizations of these methods to incorporate covariates and conclude with a general discussion of clinical trials of psychiatric therapies.

摘要

随机对照临床试验(RCT)是一项前瞻性研究,通过将受试者随机分配到治疗组,以比较一种治疗性干预措施相对于对照的效果和价值。RCT是评估新疗法在人体受试者中疗效的最具权威性的临床研究工具。在RCT中,通常感兴趣的结果是治疗或干预后直至事件发生的时间长度。在本文中,我们介绍了用于评估两组受试者反应时间模式差异的统计方法,以确定一种疗法是否优于另一种疗法。用于分析此类数据(称为生存数据)的方法集合称为生存分析。我们使用一项预防抑郁症复发的假设性临床试验的数据,说明了两种分析生存数据的基本方法。我们还讨论了将这些方法推广以纳入协变量的情况,并以对精神科疗法临床试验的一般性讨论作为结尾。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验