Family history predictors of BRCA1/BRCA2 mutation status among Tunisian breast/ovarian cancer families

Abstract

Background: With the increasing request for BRCA1/BRCA2 mutation tests, several risk models have been developed to predict the presence of mutation in these genes; in this study, we have developed an efficient BRCA genetic testing strategy.

Method: As first step, to identify predictor variables associated with BRCA status, we have undertaken a cumulative mutation analysis including data from three Tunisian studies. Then, we have developed a logistic regression model for predicting the likelihood of harboring a BRCA mutation. Using receiver operating characteristic curves (ROC), an effective evaluation was performed. A total of 92 Tunisian families were included. Overall, 27 women were positive for BRCA1/BRCA2 deleterious mutations.

Results: Tow recurrent mutations (c.211dupA and c.5266dupC) explained 76 % of BRCA1-related families and three recurrent mutations (c.1310_1313del, c.1542_1547delAAGA and c.7887_7888insA) explained 90 % of BRCA2-related families. Early age at diagnosis of breast cancer, ovarian cancer, bilateral breast cancer were associated with BRCA1, whereas male breast cancer and four or more breast cancer cases in the family were associated with BRCA2. The area under the receiver operating characteristic curve of the risk score was 0.802 (95 % confidence interval = 0.0699-0. 905).

Conclusion: Logistic regression reported particular profiles related to BRCA germline mutation carriers in our population, as well as an efficient prediction model that may be a useful tool for increasing the cost-effectiveness of genetic testing strategy.

Keywords: BRCA predictive models; BRCA1; BRCA2; Breast cancer; Predictive factors.