Mubasher Mohamed, Shan Liang, Yan Fengxia, Rivers Brian, Wu Fan, Idris Muhammed, Quarshie Alexander, Mayberry Robert M, Ofili Elizabeth, Akintobi Tabia Henry, Bae Sejong
Community Health and Preventive Medicine Department Morehouse School of Medicine, Atlanta GA.
Department of Medicine, Division of Preventive Medicine O'Neal Comprehensive Cancer Center UAB | University of Alabama at Birmingham.
Int J Epidemiol Public Health Res. 2024;5(3). Epub 2024 Sep 20.
Two of the pivotal design parameters for planning clinical trials with time-to-event outcome(s) are sample size and power. Attention needs to be placed on the hazard function (which characterizes the rate at which events occur and can be constant, decreasing, and/or increasing in time). This work employs simulation(s) of real scenarios of randomized studies to generate time-to-event variables with specific hazard characterization, obeying the Weibull function which accommodates variable hazard situations. Our aim is to determine the least required sample size and power values, based on simulating two independent samples of Weibull distributed responses, differing by various postulated hazard patterns (constant, decreasing, or increasing in time), different scale parameter values, and follow-up periods.
在规划以事件发生时间为结局的临床试验时,两个关键的设计参数是样本量和检验效能。需要关注风险函数(它描述了事件发生的速率,其在时间上可以是恒定的、递减的和/或递增的)。这项工作采用随机研究真实场景的模拟,以生成具有特定风险特征的事件发生时间变量,这些变量服从适用于可变风险情况的威布尔函数。我们的目标是,通过模拟两个服从威布尔分布的独立样本反应,基于不同的假定风险模式(在时间上恒定、递减或递增)、不同的尺度参数值和随访期,来确定所需的最小样本量和检验效能值。