Validity of models for predicting BRCA1 and BRCA2 mutations

Ann Intern Med. 2007 Oct 2;147(7):441-50. doi: 10.7326/0003-4819-147-7-200710020-00002.

Abstract

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.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / genetics*
  • Cross-Sectional Studies
  • Female
  • Genes, BRCA1*
  • Genes, BRCA2*
  • Genetic Carrier Screening*
  • Genotype
  • Humans
  • Likelihood Functions
  • Male
  • Middle Aged
  • Models, Statistical*
  • Mutation*
  • Ovarian Neoplasms / diagnosis
  • Ovarian Neoplasms / genetics*
  • Sensitivity and Specificity