Selecting a BRCA risk assessment model for use in a familial cancer clinic

BMC Med Genet. 2008 Dec 22;9:116. doi: 10.1186/1471-2350-9-116.


Background: Risk models are used to calculate the likelihood of carrying a BRCA1 or BRCA2 mutation. We evaluated the performances of currently-used risk models among patients from a large familial program using the criteria of high sensitivity, simple data collection and entry and BRCA score reporting.

Methods: Risk calculations were performed by applying the BRCAPRO, Manchester, Penn II, Myriad II, FHAT, IBIS and BOADICEA models to 200 non-BRCA carriers and 100 BRCA carriers, consecutively tested between August 1995 and March 2006. Areas under the receiver operating characteristic curves (AUCs) were determined and sensitivity and specificity were calculated at the conventional testing thresholds. In addition, subset analyses were performed for low and high risk probands.

Results: The BRCAPRO, Penn II, Myriad II, FHAT and BOADICEA models all have similar AUCs of approximately 0.75 for BRCA status. The Manchester and IBIS models have lower AUCs (0. and 0.47 respectively). At the conventional testing thresholds, the sensitivities and specificities for a BRCA mutation were, respectively, as follows: BRCAPRO (0.75, 0.62), Manchester (0.58,0.71), Penn II (0.93,0.31), Myriad II (0.71,0.63), FHAT (0.70,0.63), IBIS (0.20,0.74), BOADICEA (0.70, 0.65).

Conclusion: The Penn II model most closely met the criteria we established and this supports the use of this model for identifying individuals appropriate for genetic testing at our facility. These data are applicable to other familial clinics provided that variations in sample populations are taken into consideration.

MeSH terms

  • Adult
  • Aged
  • Breast Neoplasms / genetics*
  • Breast Neoplasms, Male / genetics
  • Case-Control Studies
  • Female
  • Genes, BRCA1*
  • Genes, BRCA2*
  • Genetic Predisposition to Disease*
  • Genetic Testing
  • Humans
  • Jews / genetics
  • Male
  • Middle Aged
  • Models, Statistical
  • Mutation
  • Ovarian Neoplasms / genetics
  • ROC Curve
  • Risk Assessment
  • Sensitivity and Specificity