Related Experiment Video
Updated: Apr 29, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
The semi-competing risk problem revisited
Ross L Prentice1, Aaron K Aragaki2
1Fred Hutchinson Cancer Center and University of Washington, Seattle, WA, USA. rprentic@whi.org.
None:
Clinical trials and cohort studies often aim to assess treatment effects or exposure associations in relation to the risk of one or more diseases, with death of the study participant as a competing risk. If the diseases under study are major health concerns, it may not be appropriate to assume that death acts as an independent source of right-censoring. When this occurs, a summary of treatment or exposure influences should consider disease incidence and death jointly. Here we consider some modeling approaches to doing so, starting with type-specific (cause-specific) hazard functions. We also model marginal hazard rates for disease-free survival and death, along with their dual outcome hazard functions, with emphasis on Cox models for each hazard function. Furthermore, a simple hazard ratio summary statistic is proposed for covariate effects on disease incidence and death jointly. Analyses of data from the Women's Health Initiative hormone therapy trials provide illustration.
Related Concept Videos
Relative Risk
Competition
Second Derivative Test: Problem Solving
Derivatives: Problem Solving
Propagation of Uncertainty from Random Error
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
