How much does genetics add to screening? Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank.

Abstract

Background The topic of whether genetic screening for cancer risk should be implemented is complex. Using UK Biobank data, we 1) computed optimal risk thresholds for the detection of breast cancer, 2) examined the overlap of high-risk individuals identified by different risk predictors, and 3) evaluated the performance of risk predictor combinations. Patients and methods We studied 246,142 women without breast cancer at study entry. Risk predictors assessed include: the Gail model (GAIL), family history of breast cancer (FH, binary), 313-SNP breast cancer polygenic risk score (PRS), and carriership of loss-of-function variants in at least one of the 9 breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51D, RAD51C, and TP53) (LoF). Absolute risk for developing invasive breast cancer was computed. Youden J-index was used to select optimal thresholds for defining high-risk. Results In total, 147,399 were considered at high risk for development of breast cancer within the next two years by at least one of the four breast cancer risk assessment tools examined (Gail2 − year>0.5%: 47%, PRS2 − year>0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only one risk predictor. Seventy-nine percent of the breast cancers that did develop within the next two years were from the high-risk group. When compared to a random sample, the biggest gain in proportion of breast cancer cases was found within women at PRS high-risk, followed by GAIL, FH and LoF. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and LoF (AUC2 − year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool appeared to increase the discriminatory ability. Conclusion Our findings suggest that risk-based breast cancer screening may require a multi-pronged approach that includes PRS, breast cancer predisposition genes, family history, and other recognized risk factors.