The relative efficiency of time-to-threshold and rate of change in longitudinal data
The relative efficiency of time-to-threshold and rate of change in longitudinal data
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DOI：
10.1016/j.cct.2011.04.007
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发表时间：
2011-09-01
影响因子：
2.2
通讯作者：
Aisen, P.
中科院分区：
文献类型：
--
作者：
Donohue, M. C.;Gamst, A. C.;Aisen, P.
随机、安慰剂对照试验通常使用事件发生时间作为主要终点，即使有疾病严重程度的连续测量。我们比较了通过纵向连续数据的线性模型估计的变化率或通过Cox比例风险模型估计的事件时间来检测治疗效果的能力。我们提出了一个分析膨胀因子来比较两种类型的分析，假设时间到事件可以表示为连续测度的时间到阈值。我们基于公开的阿尔茨海默病数据集进行模拟，其中事件发生的时间是基于一系列评估的算法定义的。将时间到事件终点的Cox比例风险模型与电池单次评估的线性模型进行比较。模拟还探讨了两种分析中基线协变量的影响。(C) 2011爱思唯尔公司版权所有。
Randomized, placebo-controlled trials often use time-to-event as the primary endpoint, even when a continuous measure of disease severity is available. We compare the power to detect a treatment effect using either rate of change, as estimated by linear models of longitudinal continuous data, or time-to-event estimated by Cox proportional hazards models. We propose an analytic inflation factor for comparing the two types of analyses assuming that the time-to-event can be expressed as a time-to-threshold of the continuous measure. We conduct simulations based on a publicly available Alzheimer's disease data set in which the time-to-event is algorithmically defined based on a battery of assessments. A Cox proportional hazards model of the time-to-event endpoint is compared to a linear model of a single assessment from the battery. The simulations also explore the impact of baseline covariates in either analysis. (C) 2011 Elsevier Inc. All rights reserved.