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A breast cancer prediction model incorporating familial and personal risk factors

Authors

  • Jonathan Tyrer,

    1. Department of Epidemiology, Mathematics and Statistics, Cancer Research U.K., Wolfson Institute of Preventive Medicine Charterhouse Square, London EC1M 6BQ, U.K.
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  • Stephen W. Duffy,

    1. Department of Epidemiology, Mathematics and Statistics, Cancer Research U.K., Wolfson Institute of Preventive Medicine Charterhouse Square, London EC1M 6BQ, U.K.
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  • Jack Cuzick

    Corresponding author
    1. Department of Epidemiology, Mathematics and Statistics, Cancer Research U.K., Wolfson Institute of Preventive Medicine Charterhouse Square, London EC1M 6BQ, U.K.
    • Department of Epidemiology, Mathematics and Statistics, Cancer Research U.K., Wolfson Institute of Preventive Medicine, Charterhouse Square, London EC1M 6BQ, U.K.
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Abstract

An Erratum has been published for this article in Statistics in Medicine 2005; 24(1):156.

Please note that the corresponding author's e-mail address has now changed. For further details please click on the link below.

DOI: 10.1002/sim.1913.

Many factors determine a woman's risk of breast cancer. Some of them are genetic and relate to family history, others are based on personal factors such as reproductive history and medical history. While many papers have concentrated on subsets of these risk factors, no papers have incorporated personal risk factors with a detailed genetic analysis. There is a need to combine these factors to provide a better overall determinant of risk. The discovery of the BRCA1 and BRCA2 genes has explained some of the genetic determinants of breast cancer risk, but these genes alone do not explain all of the familial aggregation of breast cancer. We have developed a model incorporating the BRCA genes, a low penetrance gene and personal risk factors. For an individual woman her family history is used in conjuction with Bayes theorem to iteratively produce the likelihood of her carrying any genes predisposing to breast cancer, which in turn affects her likelihood of developing breast cancer. This risk was further refined based on the woman's personal history. The model has been incorporated into a computer program that gives a personalised risk estimate. Copyright © 2004 John Wiley & Sons, Ltd.

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