Familial Cancer

, Volume 9, Issue 4, pp 495–502 | Cite as

Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of PENN II model to previous study

  • Noralane M. Lindor
  • Kiley J. Johnson
  • Hayden Harvey
  • V. Shane Pankratz
  • Susan M. Domchek
  • Katherine Hunt
  • Marcia Wilson
  • M. Cathie Smith
  • Fergus Couch


A number of models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is variable. To compare the performance characteristics of a web-based BRCA1/BRCA2 gene mutation prediction model: the PENNII model (www.afcri.upenn.edu/itacc/penn2), with studies done previously at our institution using four other models including LAMBDA, BRCAPRO, modified PENNI (Couch) tables, and Myriad II tables collated by Myriad Genetics Laboratories. Proband and family cancer history data were analyzed from 285 probands from unique families (27 Ashkenazi Jewish; 277 female) seen for genetic risk assessment in a multispecialty tertiary care group practice. All probands had clinical testing for BR.CA1 and BRCA2 mutations conducted in the same single commercial laboratory. The performance for PENNII results were assessed by the area under the receiver operating characteristic curve (AUC) of sensitivity versus 1-specificity, as a measure of ranking. The AUCs of the PENNII model were higher for predicting BRCA1 than for BRCA2 (81 versus 72%). The overall AUC was 78.7%. PENN II model for BRCA1/2 prediction performed well in this population with higher AUC compared with our experience using four other models. The ease of use of the PENNII model is compatible with busy clinical practices.


BRCA1 BRCA2 Breast cancer Risk prediction Ovarian cancer 


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Noralane M. Lindor
    • 1
  • Kiley J. Johnson
    • 1
  • Hayden Harvey
    • 1
  • V. Shane Pankratz
    • 2
  • Susan M. Domchek
    • 3
  • Katherine Hunt
    • 4
  • Marcia Wilson
    • 1
  • M. Cathie Smith
    • 5
  • Fergus Couch
    • 6
  1. 1.The Department of Medical GeneticsMayo Clinic College of MedicineRochesterUSA
  2. 2.Biomedical Statistics and InformaticsMayo Clinic College of MedicineRochesterUSA
  3. 3.Perelman Center for Advanced MedicineAbramson Cancer CenterPhiladelphiaUSA
  4. 4.Department of Hematology/OncologyMayo Clinic ArizonaScottsdaleUSA
  5. 5.Cancer Clinical Studies UnitMayo ClinicJacksonvilleUSA
  6. 6.Department of Laboratory Medicine and PathologyMayo Clinic College of MedicineRochesterUSA

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