Development and evaluation of a MIRAI 5-year risk model with a breast cancer polygenic risk score

Artificial intelligence (AI)-scores estimated from digital mammograms predict future breast cancer (BC) risk. MIRAI is a deep learning BC risk model that provides a continuous 5-year risk of overall BC from four screening full field digital mammograms. Common germline genetic variation in the form of a polygenic risk score (BC-PRS) is associated with increased BC risk and may improve MIRAI's 5-year risk prediction. Our goal was to develop an updated MIRAI 5-year risk model that incorporates the BC-PRS (MIRAI+PRS) and to evaluate its discriminatory accuracy and calibration for both overall and invasive BC compared to MIRAI alone. We developed the MIRAI+PRS model by multiplying each woman's 5-year MIRAI risk estimate by their relative risk based on their BC-PRS relative to the population mean. We evaluated the models within the Mayo Clinic Biobank mammography cohort, comprised of 12,307 women without a prior history of BC; 176 invasive and 250 overall BC were diagnosed within 5 years. MIRAI was estimated on screening mammograms closest to enrollment but at least 6 months prior to BC. Discriminatory accuracy, assessed by C-statistic, was high and similar for MIRAI+PRS vs. MIRAI models, for overall BC and invasive BC (Table). Calibration assessed by observed to expected (O/E) ratios was also similar for MIRAI+PRS compared to MIRAI predictions for BC outcomes (Table), although there was improvement in decile-specific O/E ratios across the lowest risk deciles (<1.67%) for MIRAI+PRS. Calibration for invasive cancer was poor for MIRAI with or without PRS. In summary, the MIRAI+PRS risk model did not result in significant difference of discriminatory accuracy or overall calibration compared to the MIRAI model, but there was evidence for improved calibration for women with 5-year risk below 1.67%. For invasive BC, the model had poor calibration regardless of whether PRS was included, underscoring the importance of training AI models for BC outcomes that are associated with a clinical intervention. MIRAI and MIRAI+PRS 5-year risk model performance within the Mayo Clinic Biobank mammography cohort Model HR per SD (95% CI) C-index (95% CI) Obs/Exp Ratio (95% CI) Overall BC (Invasive + DCIS), N=250 MIRAI 5 yr Risk (log) 1.69 (1.55, 1.84) 0.71 (0.68, 0.74) 0.96 (0.84, 1.09) MIRAI+PRS 5 yr Risk (log) 1.97 (1.78, 2.19) 0.72 (0.69, 0.75) 0.93 (0.82, 1.05) Invasive BC, N=176 MIRAI 5 yr Risk (log) 1.68 (1.51, 1.86) 0.71 (0.67, 0.75) 0.68 (0.58, 0.78) MIRAI+PRS 5 yr Risk (log) 1.99 (1.76, 2.24) 0.73 (0.69, 0.76) 0.66 (0.56, 0.76)