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Contemp Clin Trials. 2011 Sep;32(5):685-93. doi: 10.1016/j.cct.2011.04.007. Epub 2011 Apr 30.

The relative efficiency of time-to-threshold and rate of change in longitudinal data.

Author information

  • 1Division of Biostatistics and Bioinformatics, Department of Family and Preventive Medicine, University of California, San Diego, CA, United States. mdonohue@ucsd.edu

Abstract

Randomized, placebo-controlled trials often use time-to-event as the primary endpoint, even when a continuous measure of disease severity is available. We compare the power to detect a treatment effect using either rate of change, as estimated by linear models of longitudinal continuous data, or time-to-event estimated by Cox proportional hazards models. We propose an analytic inflation factor for comparing the two types of analyses assuming that the time-to-event can be expressed as a time-to-threshold of the continuous measure. We conduct simulations based on a publicly available Alzheimer's disease data set in which the time-to-event is algorithmically defined based on a battery of assessments. A Cox proportional hazards model of the time-to-event endpoint is compared to a linear model of a single assessment from the battery. The simulations also explore the impact of baseline covariates in either analysis.

Copyright © 2011 Elsevier Inc. All rights reserved.

PMID:
21554992
[PubMed - indexed for MEDLINE]
PMCID:
PMC3148349
Free PMC Article
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