Validity of models for predicting BRCA1 and BRCA2 mutations.

Journal Article (Journal Article;Multicenter Study)

BACKGROUND: Deleterious mutations of the BRCA1 and BRCA2 genes confer susceptibility to breast and ovarian cancer. At least 7 models for estimating the probabilities of having a mutation are used widely in clinical and scientific activities; however, the merits and limitations of these models are not fully understood. OBJECTIVE: To systematically quantify the accuracy of the following publicly available models to predict mutation carrier status: BRCAPRO, family history assessment tool, Finnish, Myriad, National Cancer Institute, University of Pennsylvania, and Yale University. DESIGN: Cross-sectional validation study, using model predictions and BRCA1 or BRCA2 mutation status of patients different from those used to develop the models. SETTING: Multicenter study across Cancer Genetics Network participating centers. PATIENTS: 3 population-based samples of participants in research studies and 8 samples from genetic counseling clinics. MEASUREMENTS: Discrimination between individuals testing positive for a mutation in BRCA1 or BRCA2 from those testing negative, as measured by the c-statistic, and sensitivity and specificity of model predictions. RESULTS: The 7 models differ in their predictions. The better-performing models have a c-statistic around 80%. BRCAPRO has the largest c-statistic overall and in all but 2 patient subgroups, although the margin over other models is narrow in many strata. Outside of high-risk populations, all models have high false-negative and false-positive rates across a range of probability thresholds used to refer for mutation testing. LIMITATION: Three recently published models were not included. CONCLUSIONS: All models identify women who probably carry a deleterious mutation of BRCA1 or BRCA2 with adequate discrimination to support individualized genetic counseling, although discrimination varies across models and populations.

Full Text

Duke Authors

Cited Authors

  • Parmigiani, G; Chen, S; Iversen, ES; Friebel, TM; Finkelstein, DM; Anton-Culver, H; Ziogas, A; Weber, BL; Eisen, A; Malone, KE; Daling, JR; Hsu, L; Ostrander, EA; Peterson, LE; Schildkraut, JM; Isaacs, C; Corio, C; Leondaridis, L; Tomlinson, G; Amos, CI; Strong, LC; Berry, DA; Weitzel, JN; Sand, S; Dutson, D; Kerber, R; Peshkin, BN; Euhus, DM

Published Date

  • October 2, 2007

Published In

Volume / Issue

  • 147 / 7

Start / End Page

  • 441 - 450

PubMed ID

  • 17909205

Pubmed Central ID

  • PMC2423214

Electronic International Standard Serial Number (EISSN)

  • 1539-3704

Digital Object Identifier (DOI)

  • 10.7326/0003-4819-147-7-200710020-00002


  • eng

Conference Location

  • United States