Value of adding single nucleotide polymorphism data to a model that predicts breast cancer risk

Eleven 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 (BCRATplus11) had an area under the receiver operating characteristic curve (AUC) of 0.637, compared to 0.607 for BCRAT. This improvement is less than from adding mammographic density to BCRAT. I also assessed how much BCRATplus11 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 BCRATplus11 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 BCRATplus11 perform substantially better than BCRAT. 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.