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Updated: Aug 21, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
[Survival analysis with competing risks: estimating failure probability]
Javier Llorca1, Miguel Delgado-Rodríguez
1Medicina Preventiva y Salud Pública. Facultad de Medicina de la Universidad de Cantabria. Santander. Spain.
Objective:
To show the impact of competing risks of death on survival analysis.
Method:
We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model.
Results:
The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks.
Conclusions:
Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.
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