Validation of a Colorectal Cancer Risk Prediction Model Among White Patients Age 50 Years and Older

Author:

Park Yikyung1,Freedman Andrew Nathan1,Gail Mitchell H.1,Pee David1,Hollenbeck Albert1,Schatzkin Arthur1,Pfeiffer Ruth M.1

Affiliation:

1. From the Division of Cancer Epidemiology and Genetics; and Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD; Information Management Systems, Rockville, MD; and AARP, Washington, DC.

Abstract

Purpose Validation of an absolute risk prediction model for colorectal cancer (CRC) by using a large, population-based cohort. Patients and Methods The National Institutes of Health (NIH) –American Association of Retired Persons (AARP) diet and health study, a prospective cohort study, was used to validate the model. Men and women age 50 to 71 years at baseline answered self-administered questionnaires that asked about demographic characteristics, diet, lifestyle, and medical histories. We compared expected numbers of CRC patient cases predicted by the model to the observed numbers of CRC patient cases identified in the NIH-AARP study overall and in subgroups defined by risk factor combinations. The discriminatory power was measured by the area under the receiver-operating characteristic curve (AUC). Results During an average of 6.9 years of follow-up, we identified 2,092 and 832 incident CRC patient cases in men and women, respectively. The overall expected/observed ratio was 0.99 (95% CI, 0.95 to 1.04) in men and 1.05 (95% CI, 0.98 to 1.11) in women. Agreement between the expected and the observed number of cases was good in most risk factor categories, except for in subgroups defined by CRC screening and polyp history. This discrepancy may be caused by differences in the question on screening and polyp history between two studies. The AUC was 0.61 (95% CI, 0.60 to 0.62) for men and 0.61 (95% CI, 0.59 to 0.62) for women, which was similar to other risk prediction models. Conclusion The absolute risk model for CRC was well calibrated in a large prospective cohort study. This prediction model, which estimates an individual's risk of CRC given age and risk factors, may be a useful tool for physicians, researchers, and policy makers.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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