Related Experiment Video
Updated: May 14, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions
Aurelien Latouche1, Arthur Allignol, Jan Beyersmann
1Conservatoire National des Arts et Métiers, IMATH, 292 Rue Saint Martin, Case 441, EA4629 Paris, France. aurelien.latouche@cnam.fr
Abstract:
Competing risks endpoints are frequently encountered in hematopoietic stem cell transplantation where patients are exposed to relapse and treatment-related mortality. Both cause-specific hazards and direct models for the cumulative incidence functions have been used for analyzing such competing risks endpoints. For both approaches, the popular models are of a proportional hazards type. Such models have been used for studying prognostic factors in acute and chronic leukemias. We argue that a complete understanding of the event dynamics requires that both hazards and cumulative incidence be analyzed side by side, and that this is generally the most rigorous scientific approach to analyzing competing risks data. That is, understanding the effects of covariates on cause-specific hazards and cumulative incidence functions go hand in hand. A case study illustrates our proposal.
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Hazard Rate
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, controlled...
Assumptions of Survival Analysis
Hazard Ratio
For example, in a clinical trial evaluating a...
Cancer Survival Analysis

