BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors.

Abstract

Purpose: Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the BOADICEA risk model to incorporate the effects of Polygenic Risk Scores (PRS) and other risk factors (RFs). Methods: BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2 and ATM; a PRS based on 313 SNPs explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs and mammographic density, while allowing for missing information. Results: Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th. 14.7% of women are predicted to have a lifetime risk of 17%-<30% (moderate risk according to NICE guidelines) and 1.1% a lifetime risk of 30% (high risk). Conclusions: This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualised, informed decision-making on prevention therapies and screening