Terry MB, et al. - Researchers performed this validation study assessing the relative performance of four commonly used models of breast cancer risk and investigating the effect of limited data input on each one's performance. From the Breast Cancer Prospective Family Study Cohort (ProF-SC), that included 18,856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, they selected women who were 20–70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. Using this elected cohort, they compared four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). As per results, models including multigenerational family history, such as BOADICEA and IBIS, show the superior predictive ability for breast cancer risk, even for women at average or below-average risk of breast cancer. BOADICEA and IBIS performed similarly, however, there appeared a possibility for further improvements in the accuracy of predictions with hybrid models that incorporate the polygenic risk component of BOADICEA and the non-family-history risk factors included in IBIS.