Ma Xiangmei, Cheung Yin Bun
Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
Programme in Health Services & Systems Research, Duke-NUS Medical School, Singapore, Singapore.
J Biopharm Stat. 2025 Jan 2;35(1):70-84. doi: 10.1080/10543406.2023.2275755. Epub 2023 Nov 6.
Clinical trialists have long been searching for approaches to increase statistical power without increasing sample size. Conventional wait-list controlled (WLC) trials are limited to two trial arms and two or three repeated measurements per person. These features limit statistical power. Furthermore, their analysis is usually based on analysis of covariance or mixed effects modelling, with a focus on estimating treatment effect at one time-period after initiation of therapy. We propose two 3-arm WLC trial designs together with a mixed-effects analysis framework. The designs require three or four repeated measurements per person. The analytic framework defines up to three treatment effect estimands, representing the effects at one to three time-periods after initiation of therapy. The precision (inverse of variance) of the treatment effect estimators in the new and conventional trial designs are analytically derived and evaluated in simulations. The results are interpreted in the context of a cognitive training trial in older people. The proposed designs and analysis methods increase the precision level of treatment effect estimators as compared to conventional designs and analyses. Given a target level of statistical power, the proposed methods require a smaller number of participants per trial than the conventional methods, without necessarily increasing the number of measurements per trial. Furthermore, the proposed analytic framework sheds light on the treatment effects at different times after initiation of therapy, which is not usually considered in conventional WLC trial analysis. In situations that a WLC trial is appropriate, the 3-arm designs are useful alternatives to existing 2-arm designs.
长期以来,临床试验人员一直在寻找在不增加样本量的情况下提高统计效能的方法。传统的等待列表对照(WLC)试验仅限于两个试验组,且每人进行两到三次重复测量。这些特点限制了统计效能。此外,其分析通常基于协方差分析或混合效应建模,重点是估计治疗开始后一个时间段的治疗效果。我们提出了两种三臂WLC试验设计以及一个混合效应分析框架。这些设计要求每人进行三到四次重复测量。该分析框架定义了多达三个治疗效果估计值,代表治疗开始后一到三个时间段的效果。通过模拟分析得出并评估了新的和传统试验设计中治疗效果估计器的精度(方差的倒数)。在一项针对老年人的认知训练试验的背景下对结果进行了解释。与传统设计和分析相比,所提出的设计和分析方法提高了治疗效果估计器的精度水平。在给定的统计效能目标水平下,所提出的方法与传统方法相比,每次试验所需的参与者数量更少,且不一定会增加每次试验的测量次数。此外,所提出的分析框架揭示了治疗开始后不同时间的治疗效果,这在传统WLC试验分析中通常未被考虑。在适合进行WLC试验的情况下,三臂设计是现有两臂设计的有用替代方案。