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Predicting the absolute risk of dying from colorectal cancer and from other causes using population‐based cancer registry data
Author(s) -
Lee Minjung,
Cronin Kathleen A.,
Gail Mitchell H.,
Feuer Eric J.
Publication year - 2011
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4454
Subject(s) - colorectal cancer , cancer registry , covariate , statistics , imputation (statistics) , population , cancer , medicine , missing data , calibration , computer science , epidemiology , econometrics , data mining , mathematics , environmental health
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.