Predicting the absolute risk of dying from colorectal cancer and from other causes using population-based cancer registry data


Minjung Lee, Data Analysis and Interpretation Branch, Division of Cancer Control and Population Studies, National Cancer Institute, Bethesda, MD 20852, USA.



This paper describes how population cancer registry data from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute can be used to develop a prognostic model to predict the absolute risk of mortality from cancer and from other causes for an individual with specific covariates. It incorporates previously developed methods for competing risk modeling along with an imputation method to address missing cause of death information. We illustrate these approaches with colorectal cancer and evaluate the model discriminatory and calibration accuracy by time-dependent area under the receiver operating characteristic curve and calibration plot. Copyright © 2011 John Wiley & Sons, Ltd.