Estimating a treatment effect with repeated measurements accounting for varying effectiveness duration

• 成果类型: Article
• 署名作者: Chen, Y. Q.; Yang, J.; Cheng, S.; Jackson, J. B.
• 署名单位: Fred Hutchinson Cancer Center; University of California System; University of California Berkeley; University of California System; University of California Berkeley; University of California System; University of California San Francisco; Johns Hopkins University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asm019
• 发表日期: 2007
• 页码: 387402
• 关键词: Longitudinal Data; regression-analysis; coefficient models; covariance structure; nuisance parameter; drug-resistance; survival-data; time; nevirapine; pharmacokinetics

摘要

To assess treatment efficacy in clinical trials, certain clinical outcomes are repeatedly measured over time for the same subject. The difference in their means may characterize a treatment effect. Since treatment effectiveness lag and saturation times may exist, erosion of treatment effect often occurs during the observation period. Instead of using models based on ad hoc parametric or purely nonparametric time-varying coefficients, we model the treatment effectiveness durations, which are the time intervals between the lag and saturation times. Then we use some mean response models to include such treatment effectiveness durations. Our methodology is demonstrated by simulations and analysis of a landmark HIV/AIDS clinical trial of short-course nevirapine against mother-to-child HIV vertical transmission during labour and delivery.