An introduction to survival analysis: statistical methods for analysis of clinical trial data.
An introduction to survival analysis: statistical methods for analysis of clinical trial data.
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生存分析简介：临床试验数据分析的统计方法。
DOI：
10.1037//0022-006x.57.4.536
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发表时间：
1989
影响因子：
5.9
通讯作者：
Bromberg,J
中科院分区：
文献类型：
--
作者：
Greenhouse,JB;Stangl,D;Bromberg,J
随机对照临床试验（RCT）是一项前瞻性研究，将受试者随机分配至治疗组，以比较治疗干预与对照的效果和价值。随机对照试验是评价新疗法在人类受试者中疗效的最权威的临床研究工具。RCT中关注的结果通常是治疗或干预后事件发生的时间长度。在这篇文章中，我们介绍了统计方法来评估两组受试者之间的反应时间模式的差异，以确定一种治疗是否优于另一种。用于分析这些数据的方法的集合，称为生存数据，称为生存分析。使用的数据从一个假设的临床试验，预防复发的抑郁症，我们说明了两个基本的方法来分析生存数据。我们还讨论了这些方法的概括，纳入协变量，并得出结论，精神病治疗的临床试验的一般性讨论。
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.