1506 Background: Specific clinical interventions in BRCA mutation carriers reduces the risk of breast and ovarian cancers and may improve survival; thus,identification of mutation carriers is important. The sensitivity of current BRCA mutation testing is unclear as a “gold standard” test is lacking. We assessed the BRCA1 mutation detection rate with current comprehensive clinical testing using linkage analysis as the comparator. Methods: 26 families with linkage analyses results available were included in this analysis. BRCAPRO, BOADICEA, and other risk estimation models were applied. Maximum-likelihood linkage analyses were performed to compute two-point and multipoint LOD scores using previously described BRCA1 –linked genetic markers; scores were classified as linked, not linked, or suggestive. At least one individual from each family underwent comprehensive testing. Results: Of 26 families analyzed, 9 demonstrated linkage and 4 demonstrated suggestive linkage to BRCA1. Of these 13 families, 12 were found to have BRCA1 mutations: a detection rate of 92.3%. In 3 of these 12 families, genetic mutation testing performed prior to large genomic rearrangement (LGR) testing was negative, demonstrating an improved detection rate with LGR testing which in this series was 23%. The 12 families with higher LOD scores and positive mutation testing had high mean prior probabilities by all models. Families which were not linked and who tested negative for mutations had lower mean prior probabilities. In one family, disease demonstrated linkage with a two-point LOD score of 1.59 and multipoint LOD of 0.85 and all risk estimation models yielded high prior probabilities. Despite this, mutation testing was negative by full sequencing and MLPA analysis. Conclusions: When evaluated in a sample of families from high-risk clinics, current comprehensive testing compares well to linkage data. The inclusion of LGR testing has improved the mutation detection capability of clinical testing; however, some mutations may still be missed. Negative mutation testing results should be interpreted in the context of family history and prior probability during counseling. Despite recent advances, further improvements in genetic testing are warranted.
Radiation risk estimation models.
