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J Clin Oncol. 2009 Feb 10;27(5):686-93. doi: 10.1200/JCO.2008.17.4797. Epub 2008 Dec 29.

Colorectal cancer risk prediction tool for white men and women without known susceptibility.

Author information

  • 1Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, EPN 4005 MSC 7344, Bethesda, MD 20892-7344, USA. Andrew_Freedman@nih.gov

Abstract

PURPOSE:

Given the high incidence of colorectal cancer (CRC), and the availability of procedures that can detect disease and remove precancerous lesions, there is a need for a model that estimates the probability of developing CRC across various age intervals and risk factor profiles.

METHODS:

The development of separate CRC absolute risk models for men and women included estimating relative risks and attributable risk parameters from population-based case-control data separately for proximal, distal, and rectal cancer and combining these estimates with baseline age-specific cancer hazard rates based on Surveillance, Epidemiology, and End Results (SEER) incidence rates and competing mortality risks.

RESULTS:

For men, the model included a cancer-negative sigmoidoscopy/colonoscopy in the last 10 years, polyp history in the last 10 years, history of CRC in first-degree relatives, aspirin and nonsteroidal anti-inflammatory drug (NSAID) use, cigarette smoking, body mass index (BMI), current leisure-time vigorous activity, and vegetable consumption. For women, the model included sigmoidoscopy/colonoscopy, polyp history, history of CRC in first-degree relatives, aspirin and NSAID use, BMI, leisure-time vigorous activity, vegetable consumption, hormone-replacement therapy (HRT), and estrogen exposure on the basis of menopausal status. For men and women, relative risks differed slightly by tumor site. A validation study in independent data indicates that the models for men and women are well calibrated.

CONCLUSION:

We developed absolute risk prediction models for CRC from population-based data, and a simple questionnaire suitable for self-administration. This model is potentially useful for counseling, for designing research intervention studies, and for other applications.

PMID:
19114701
[PubMed - indexed for MEDLINE]
PMCID:
PMC2645090
Free PMC Article

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