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Biometrika Advance Access originally published online on February 28, 2007
Biometrika 2007 94(2):387-402; doi:10.1093/biomet/asm019
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Copyright © 2007 Biometrika Trust

Articles

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

Y. Q. Chen, J. Yang, S. Cheng and J. B. Jackson

Program in Biostatistics, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, U.S.A.
Divisions of Biostatistics & Epidemiology, School of Public Health, University of California, Berkeley, California 94720, U.S.A.
Department of Biostatistics & Epidemiology, University of California, San Francisco, California 94143, U.S.A.
Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21205, U.S.A.

yqchen{at}scharp.org

jingrong{at}stat.berkeley.edu

scheng{at}biostat.ucsf.edu

bjackso{at}jhmi.edu

Received for publication 1 November 2005. Revision received 1 June 2006.
  Abstract

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.

Key Words: effect erosion • HIV/AIDS clinical trial • longitudinal study • mean response model • time-varying coefficient


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