Breast Cancer Risk Assessment Using the OncoVue® Model

Abstract

Breast cancer is a complex disease with risk determined by both genetic and clinical risk factors. Inherited germline mutations in genes such as BRCA1/2, TP53 and PTEN strongly contribute to breast cancer risk but are very rare and not relevant to clinical risk evaluation for most women. Although, the Breast Cancer Risk Assessment Tool (BCRAT or Gail model) which employs only clinical risk factors has been shown to perform poorly at individualized risk estimation, it has been the only risk model available for the majority of women. More recently, OncoVue ® , a logistic regression model developed from analyzing individual genetic and clinical factor data from a large case-control study has been developed. The current communication summarizes and reviews the data presented to date concerning the development and performance of the model. In several sample sets OncoVue has significantly outperformed the BCRAT in accurately estimating risk. Together these studies demonstrate the improved ability of OncoVue to produce more accurate individualized breast cancer risk estimation indicating it is more clinically useful for directing screening and prevention decisions.