Luo Xiaodong, Huang Bo, Quan Hui
Department of Biostatistics and Programming, Research and Development, Sanofi U.S., Bridgewater, NJ, USA.
Pfizer Inc., New London, CT, USA.
Clin Trials. 2019 Dec;16(6):616-625. doi: 10.1177/1740774519871447. Epub 2019 Aug 26.
BACKGROUND/AIMS: Restricted mean survival time has become a popular treatment effect measurement because of its nice interpretability. However, study design based on restricted mean survival times often requires extensive simulation studies as the variance structure is hard to obtain analytically. This article aims to provide a flexible approach to conduct study design and monitoring based on the restricted mean survival times without resorting to simulation.
We assume that both the event time and censoring time distributions are piecewise exponential, and the accrual distribution is piecewise uniform, with which the restricted mean survival times and their variance-covariance structure can be conveniently computed.
Since we allow arbitrary number of pieces in the piecewise exponential and uniform distributions, the resulting model can handle a wide range of scenarios. The usefulness of the approach is demonstrated via an example.
The proposed approach is flexible and useful in the design and monitoring of survival trials based on restricted mean survival times.
背景/目的:受限平均生存时间因其良好的可解释性已成为一种常用的治疗效果测量指标。然而,基于受限平均生存时间的研究设计通常需要进行大量的模拟研究,因为其方差结构难以通过解析方法获得。本文旨在提供一种灵活的方法,无需借助模拟即可基于受限平均生存时间进行研究设计和监测。
我们假设事件时间和删失时间分布均为分段指数分布,且入组分布为分段均匀分布,据此可方便地计算受限平均生存时间及其方差-协方差结构。
由于我们允许分段指数分布和均匀分布中的分段数任意,因此所得模型能够处理多种情况。通过一个例子展示了该方法的实用性。
所提出的方法在基于受限平均生存时间的生存试验设计和监测中灵活且有用。