Optimal selection for BRCA1 and BRCA2 mutation testing using a combination of ' easy to apply ' probability models

To establish an efficient, reliable and easy to apply risk assessment tool to select families with breast and/or ovarian cancer patients for BRCA mutation testing, using available probability models. In a retrospective study of 263 families with breast and/or ovarian cancer patients, the utility of the Frank (Myriad), Gilpin (family history assessment tool) and Evans (Manchester) model was analysed, to select 49 BRCA mutation-positive families. For various cutoff levels and combinations, the sensitivity and specificity were calculated and compared. The best combinations were subsequently validated in additional sets of families. Comparable sensitivity and specificity were obtained with the Gilpin and Evans models. They appeared to be complementary to the Frank model. To obtain an optimal sensitivity, five ‘additional criteria' were introduced that are specific for the selection of small or uninformative families. The optimal selection is made by the combination ‘Frank ⩾16% or Evans2 ⩾12 or one of five additional criteria'. The efficiency of the selection of families for mutation testing of BRCA1 and BRCA2 can be optimised by using a combination of available easy to apply risk assessment models

The BRCAPRO 5.0 model is a useful tool in genetic counseling and clinical management of male breast cancer cases

No study has evaluated the performance of BRCA1/2 mutations prediction models in male breast cancer (MBC) series. Although rare, MBC deserves attention because male and female breast cancers share many characteristics, including the involvement of genetic predisposition factors such as BRCA1/BRCA2 mutations. Indeed, the occurrence of MBC is a commonly used criterion to select families for BRCA mutation testing. We evaluated the performance and clinical effectiveness of four different predictive models in a population-based series of 102 Italian MBC patients characterized for BRCA1/2 mutations. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for each risk model at the 10% threshold. The area under the ROC (AUC) curves and its corresponding asymptotic 95% CIs were calculated as a measure of the accuracy. In our study, the BRCAPRO version 5.0 had the highest combination of sensitivity, specificity, NPV and PPV for the combined probability and for the discrimination of BRCA2 mutations. In individuals with negative breast–ovarian cancer family history, BRCAPRO 5.0 reached a high discriminatory capacity (AUC=0.92) in predicting BRCA2 mutations and showed values of sensitivity, specificity, NPV and PPV of 0.5, 0.98, 0.97 and 0.67, respectively, for the combined probability. BRCAPRO version 5.0 can be particularly useful in dealing with non-familial MBC, a circumstance that often represents a challenging situation in genetic counseling