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Genetic Variants Help Little in Breast Cancer Risk Model

Including genetic variants changes risk prediction only slightly, if at all, in most women

WEDNESDAY, March 17 (HealthDay News) -- Adding recently discovered common genetic variants to traditional risk models for breast cancer makes only a modest improvement in predictive value, according to research published in the March 18 issue of the New England Journal of Medicine.

Sholom Wacholder, Ph.D., of the National Cancer Institute in Bethesda, Md., and colleagues performed an analysis of combined data from five studies totaling 5,590 women with breast cancer, and a control group of 5,998 healthy women. The researchers compared the predictive accuracy of the Gail model -- the most commonly used breast cancer risk model -- against a model based on 10 common single-nucleotide polymorphisms (SNPs) that recently have been found to be associated with breast cancer, as well as a model combining both sets of factors.

The researchers found that the SNP model was as good as the Gail model alone, while the model using both SNPs and traditional factors was only slightly better than either model alone. The combined model reclassified 26 percent of women to higher risk, 28 percent to lower risk, and left 46 percent with risk unchanged, and the shifts were judged too minor to affect clinical decision-making.

"The inclusion of newly discovered genetic factors modestly improved the performance of risk models for breast cancer. The level of predicted breast-cancer risk among most women changed little after the addition of currently available genetic information," the authors write.

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