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.

Feb 15, 2009 - BRCAPRO implements a Mendelian computational model based on a piece of software called BayesMendel. BRCAPRO calculation are used.

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. Introduction Several models have been developed to assess the pre-test probability of identifying BRCA1/2 germline mutations in individuals at risk for hereditary breast and ovarian cancer.

Materials and methods In this study, we evaluated the performance and clinical effectiveness of the above-described prediction models in a population-based series of 102 male patients affected by invasive BC and characterized for BRCA1/ 2 mutations. The recruitment of the cases and the BRCA1/2 mutational analysis were carried out as recently described., Briefly, the recruitment of all incident MBC cases was based on all currently available local sources (including pathology departments and the hospital discharge database). For each case index the entire coding sequence and each intron–exon boundary were screened for germline mutations by combining the protein truncation test (PTT), single-strand conformation polymorphism (SSCP), multiplex ligation-dependent probe amplification (MLPA) and direct sequencing. All MBC cases, diagnosed in the period 1991–2007, were resident in Eastern Tuscany (mean age at diagnosis 63.6±12.0 years). For each study participant we obtained detailed information on his personal and familial history for cancer at any site.

All information was collected by a geneticist and validated by relevant sources, mainly local cancer and mortality registries. Overall, 38% (39/102) of the patients reported a first- and/or second-degree breast–ovarian cancer FH, eight cases (8/102, 7.8%) carried a BRCA2 mutation and two cases (2/102, 2.0%) carried the same founder BRCA1 mutation., Six of the 10 mutation carriers had a positive FH. Kryak dlya corel draw x6. Thus, mutation carriers account for 15.4% (6/39) of our male probands with a positive FH and for 6.4% (4/63) of those without a positive FH.

For each proband we applied the Myriad II, FHAT, IC software version 3.4, and BRCAPRO models by using the CaGene version 4.2 and 5.0 software packages. The IC software utilizes country customized allele frequencies and penetrances obtained from Italian breast ovarian cancer families.

In version 4.2 the genetic parameters have been updated as described by Chen et al. Version 5.0 of BRCAPRO has been recently updated by using new penetrance curves based on nine meta-analysis studies and by using male penetrance estimates based on the largest US cohort., Moreover, breast cancer biomarkers have been included. All these models, except for Myriad and FHAT, give a composite probability as well as a BRCA1 or BRCA2 probability. We focused on evaluating the performance of the models that are frequently and easily used in clinical practice at our Institute and that can run through the CancerGene freeware counselling package.,, Sensitivity, specificity, PPV and NPV were calculated for each risk model at the 10% threshold. For the FHAT model this threshold corresponds to a cut-off score of 10 points.

We rescaled the FHAT score as suggested by Parmigiani et al. The area under the ROC (AUC) curves and its corresponding asymptotic 95% CI were calculated as a measure of the accuracy of the model. Results As shown by AUC estimates (), all Mendelian models, but not empirical models, performed equally well, and their ability to discriminate between mutation-carrying and non-carrying probands was similar. On comparing the sensitivity, specificity, PPV and NPV, we observed that NPV was very high for all models (range 0.97–1.0).