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

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

    Source

    Division 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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