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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
SAS macros for estimation of the cumulative incidence functions based on a Cox regression model for competing risks
Susanne Rosthøj1, Per K Andersen, Steen Z Abildstrom
1Department of Biostatistics, University of Copenhagen, Blegdamsvej 3, DK 2200 Copenhagen N, Denmark.
Abstract:
When considering competing risks survival data, the cause specific hazard functions are often modelled by the proportional hazards Cox regression model. First, we present how to estimate the parameters in this model when some of the covariates are allowed to have exactly the same effect on several causes of failure. In many cases, the focus is not on the parameter estimates, but rather on the probability of observing a failure from a specific cause for individuals with specified covariate values. These probabilities, the cumulative incidences, are not simple functions of the parameters and they are, so far, not provided by the standard statistical software packages. We present two SAS macros: a SAS macro named CumInc for estimation of the cumulative incidences and a SAS macro named CumIncV for estimation of the cumulative incidences and the variances of the estimated cumulative incidences. The use of the macros is demonstrated through an example.
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