Improving the accuracy of BRCA1/2 mutation prediction: Validation of the novel country-customized IC software

Carlo Capalbo, Enrico Ricevuto, Annarita Vestri, Tina Sidoni, Amelia Buffone, Enrico Cortesi, Paolo Marchetti, Giovanni Scambia, Silverio Tomao, Christian Rinaldi, Massimo Zani, Sergio Ferraro, Luigi Frati, Isabella Screpanti, Alberto Gulino, Giuseppe Giannini

Research output: Contribution to journalArticle

Abstract

Inherited mutations of the BRCA1/2 genes confer a significantly increased risk for breast and/or ovarian cancer development. Several models were elaborated to help genetic counsellors in selecting individuals with high probability of being mutation carriers. The IC software, a country-customized version of the Brcapro model, was recently shown to be particularly accurate in the prediction of carrier probability status in the Italian population. Here, we used our independent series of 70 breast/ovarian cancer families to analyze the performances of the IC software and compare it to widely used models, such as Brcapro and the Myriad mutation prevalence tables. Analysis of the areas under the receiver operator characteristics (ROC) curves indicated that overall the models performed well. However, the IC software and Myriad tables were more efficient in predicting mutated cases, showing a higher sensitivity (94 and 88%, respectively) and negative predictive value (NPV, 94 and 92%, respectively) compared to Brcapro (sensitivity 71 and NPV 83%). IC software also appeared particularly accurate in the identification of families belonging the low mutation risk group (

Original languageEnglish
Pages (from-to)49-54
Number of pages6
JournalEuropean Journal of Human Genetics
Volume14
Issue number1
DOIs
Publication statusPublished - Jan 2006

Keywords

  • BRCA1
  • BRCA2
  • Brcapro
  • Breast/ovarian cancer
  • IC software
  • Predictive models

ASJC Scopus subject areas

  • Genetics(clinical)

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    Capalbo, C., Ricevuto, E., Vestri, A., Sidoni, T., Buffone, A., Cortesi, E., Marchetti, P., Scambia, G., Tomao, S., Rinaldi, C., Zani, M., Ferraro, S., Frati, L., Screpanti, I., Gulino, A., & Giannini, G. (2006). Improving the accuracy of BRCA1/2 mutation prediction: Validation of the novel country-customized IC software. European Journal of Human Genetics, 14(1), 49-54. https://doi.org/10.1038/sj.ejhg.5201511