Related Experiment Video
Updated: Apr 6, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Competing risk bias was common in Kaplan-Meier risk estimates published in prominent medical journals
Carl van Walraven1, Finlay A McAlister2
1Faculty of Medicine, University of Ottawa; Epidemiology and Community Medicine, University of Ottawa; Ottawa Hospital Research Institute; ICES uOttawa.
Objective:
Risk estimates from Kaplan-Meier curves are well known to medical researchers, reviewers, and editors. In this study, we determined the proportion of Kaplan-Meier analyses published in prominent medical journals that are potentially biased because of competing events ("competing risk bias").
Study Design And Setting:
We randomly selected 100 studies that had at least one Kaplan-Meier analysis and were recently published in prominent medical journals. Susceptibility to competing risk bias was determined by examining the outcome and potential competing events. In susceptible studies, bias was quantified using a previously validated prediction model when the number of outcomes and competing events were given.
Results:
Forty-six studies (46%) contained Kaplan-Meier analyses susceptible to competing risk bias. Sixteen studies (34.8%) susceptible to competing risk cited the number of outcomes and competing events; in six of these studies (6/16, 37.5%), the outcome risk from the Kaplan-Meier estimate (relative to the true risk) was biased upward by 10% or more.
Conclusion:
Almost half of Kaplan-Meier analyses published in medical journals are susceptible to competing risk bias and may overestimate event risk. This bias was found to be quantitatively important in a third of such studies.
Related Concept Videos
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Assumptions of Survival Analysis
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
The Mantel-Cox Log-Rank Test

