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University of Cambridge > Talks.cam > MRC Biostatistics Unit Seminars > The Value for Medical and Public Health Decisions of Adding Single Nucleotide Polymorphism Data to a Model for Breast Cancer Risk
The Value for Medical and Public Health Decisions of Adding Single Nucleotide Polymorphism Data to a Model for Breast Cancer RiskAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Michael Sweeting. Seven single nucleotide polymorphisms (SNPs) have recently been confirmed to be associated with breast cancer. I assessed the value of adding these SNPs to the Breast Cancer Risk Assessment Tool (BCRAT), which is based on ages at menarche and at first live birth, family history of breast cancer, and history of breast biopsy examinations. The model with these SNPs (BCRATplus7) had an area under the receiver operating characteristic curve (AUC) of 0.632, compared to 0.607 for BCRAT . This improvement is less than from adding mammographic density to BCRAT . I also assessed how much BCRA Tplus7 reduced expected losses in deciding whether a woman should take tamoxifen to prevent breast cancer and in deciding whether a woman should have a mammogram. In addition, I examined whether BCRA Tplus7 was more effective than BCRAT in allocating a scarce public health resource, such as access to mammography, based on ranking women on their breast cancer risk and allocating the resource to those at highest risk. In none of these applications did BCRA Tplus7 perform substantially better than BCRAT . A cross-classification of risk by the two models indicated that some women would change risk categories, depending on the risk threshold, if BCRA Tplus7 were used instead of BCRAT , but it is not known if BCRA Tplus7 is well calibrated. These results were hardly changed if three additional very recently identified SNPs were added. I conclude that the available SNPs do not improve the performance of models to estimate breast cancer risk enough to warrant their use outside the research setting. This talk is part of the MRC Biostatistics Unit Seminars series. This talk is included in these lists:
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