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Updated: Jun 19, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A robust method for comparing two treatments in a confirmatory clinical trial via multivariate time-to-event methods
Benjamin R Saville1, Amy H Herring, Gary G Koch
1Department of Biostatistics, Vanderbilt University School of Medicine, S-2323 Medical Center North, Nashville, TN 37232-2158, USA. b.saville@vanderbilt.edu
Abstract:
We consider regulatory clinical trials that require a prespecified method for the comparison of two treatments for chronic diseases (e.g. Chronic Obstructive Pulmonary Disease) in which patients suffer deterioration in a longitudinal process until death occurs. We define a composite endpoint structure that encompasses both the longitudinal data for deterioration and the time-to-event data for death, and use multivariate time-to-event methods to assess treatment differences on both data structures simultaneously, without a need for parametric assumptions or modeling. Our method is straightforward to implement, and simulations show that the method has robust power in situations in which incomplete data could lead to lower than expected power for either the longitudinal or survival data. We illustrate the method on data from a study of chronic lung disease.
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