To establish whether existing mutation prediction models can identify which male breast cancer (MBC) patients should be offered BRCA1 and BRCA2 diagnostic DNA screening, we compared the performance of BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm), BRCAPRO (BRCA probability) and the Myriad prevalence table ("Myriad"). These models were evaluated using the family data of 307 Dutch MBC probands tested for BRCA1/2, 58 (19%) of whom were carriers. We compared the numbers of observed vs predicted carriers and assessed the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) for each model. BOADICEA predicted the total number of BRCA1/2 mutation carriers quite accurately (observed/predicted ratio: 0.94). When a cut-off of 10% and 20% prior probability was used, BRCAPRO showed a non-significant better performance (observed/predicted ratio BOADICEA: 0.81, 95% confidence interval [CI]: [0.60-1.09] and 0.79, 95% CI: [0.57-1.09], vs. BRCAPRO: 1.02, 95% CI: [0.75-1.38] and 0.94, 95% CI: [0.68-1.31], respectively). Myriad underestimated the number of carriers in up to 69% of the cases. BRCAPRO showed a non-significant, higher AUC than BOADICEA (0.798 vs 0.776). Myriad showed a significantly lower AUC (0.671). BRCAPRO and BOADICEA can efficiently identify MBC patients as BRCA1/2 mutation carriers. Besides their general applicability, these tools will be of particular value in countries with limited healthcare resources.

Additional Metadata
Keywords BOADICEA, BRCA1, BRCA2, BRCAPRO, Male breast cancer, Myriad prevalence table
Persistent URL dx.doi.org/10.1111/cge.13065, hdl.handle.net/1765/102276
Journal Clinical Genetics: an international journal of genetics and molecular medicine
Citation
Moghadasi, S, Grundeken, V. (V.), Janssen, L.A.M. (L. A.M.), Dijkstra, N.H. (N. H.), Rodríguez-Girondo, M. (M.), van Zelst-Stams, W.A, … van Asperen, C.J. (C. J.). (2017). Performance of BRCA1/2 mutation prediction models in male breast cancer patients. Clinical Genetics: an international journal of genetics and molecular medicine. doi:10.1111/cge.13065