Accuracy of risk prediction models for breast cancer and BRCA1/BRCA2 mutation carrier probabilities in Israel

Efrat Schwarz Kenan, Michael Friger, Daphna Shochat-Bigon, Hagit Schayek, Rinat Bernstein-Molho, Eitan Friedman

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background/Aim: Several algorithms have been developed to assess the risk of predicting BRCA mutation and breast cancer (BC) risk. The aim of this study was to evaluate the accuracy of these prediction algorithms in the Israeli population. Patients and Methods: Risk for developing breast cancer and the probability for carrying BRCA1/2 mutations using BOADICEA, BRCAPRO, IBIS, MYRIAD and PENN2 models were computed for individuals counseled and genotyped at the Oncogenetics unit in 2000 and 2005. The predicted mutation carriers and BC risks were compared with actual carrier rates by genotyping and BC diagnoses derived from the Israeli National Cancer Registry database. Results: Overall, 65/648 (10%) study participants were BRCA1/2 mutation carriers. Of 373 cancer-free participants at counseling, 25 had breast cancer by 2016. BOADICEA and BRCAPRO performed best for predicting BRCA mutation (AUC=0.741, 0.738, respectively). No model was clinically useful in predicting breast cancer risk. Conclusion: BOADICEA and BRCAPRO outperformed the other tested algorithms in BRCA mutation prediction in Israeli women, but none was valuable in breast cancer risk prediction.

Original languageEnglish
Pages (from-to)4557-4563
Number of pages7
JournalAnticancer Research
Issue number8
StatePublished - 1 Aug 2018


  • Breast cancer risk
  • Prediction algorithms
  • Risk factors

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


Dive into the research topics of 'Accuracy of risk prediction models for breast cancer and BRCA1/BRCA2 mutation carrier probabilities in Israel'. Together they form a unique fingerprint.

Cite this