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Updated: Feb 16, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Modeling the cumulative incidence function of multivariate competing risks data allowing for within-cluster
Luise Cederkvist1, Klaus K Holst2, Klaus K Andersen3
1Section of Biostatistics, University of Copenhagen, Øster Farimagsgade 5B, DK-1014 Copenhagen K, Denmark and Unit of Statistics & Pharmacoepidemiology, Danish Cancer Society Research Center, Strandboulevarden 49, DK-2100 Copenhagen Ø, Denmark.
Abstract:
We propose to model the cause-specific cumulative incidence function of multivariate competing risks data using a random effects model that allows for within-cluster dependence of both risk and timing. The model contains parameters that makes it possible to assess how the two are connected, e.g. if high-risk is related to early onset. Under the proposed model, the cumulative incidences of all failure causes are modeled and all cause-specific and cross-cause associations specified. Consequently, left-truncation and right-censoring are easily dealt with. The proposed model is assessed using simulation studies and applied in analysis of Danish register-based family data on breast cancer.
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