Validation of a breast cancer risk prediction model based on the key risk factors: family history, mammographic density and polygenic risk

Purpose We compared a simple breast cancer risk prediction model, BRISK (which includes mammographic density, polygenic risk and clinical factors), against a similar model with more risk factors (simplified Rosner) and against two commonly used clinical models (Gail and IBIS). Methods Using nested case–control data from the Nurses’ Health Study, we compared the models’ association, discrimination and calibration. Classification performance was compared between Gail and BRISK for 5-year risks and between IBIS and BRISK for remaining lifetime risk. Results The odds ratio per standard deviation was 1.43 (95% CI 1.32, 1.55) for BRISK 5-year risk, 1.07 (95% CI 0.99, 1.14) for Gail 5-year risk, 1.72 (95% CI 1.59, 1.87) for simplified Rosner 10-year risk, 1.51 (95% CI 1.41, 1.62) for BRISK remaining lifetime risk and 1.26 (95% CI 1.16, 1.36) for IBIS remaining lifetime risk. The area under the receiver operating characteristic curve (AUC) was improved for BRISK over Gail for 5-year risk ( AUC = 0.636 versus 0.511, P < 0.0001) and for BRISK over IBIS for remaining lifetime risk ( AUC = 0.647 versus 0.571, P < 0.0001). BRISK was well calibrated for the estimation of both 5-year risk (expected/observed [ E/O ] = 1.03; 95% CI 0.73, 1.46) and remaining lifetime risk ( E/O = 1.01; 95% CI 0.86, 1.17). The Gail 5-year risk ( E/O = 0.85; 95% CI 0.58, 1.24) and IBIS remaining lifetime risk ( E/O = 0.73; 95% CI 0.60, 0.87) were not well calibrated, with both under-estimating risk. BRISK improves classification of risk compared to Gail 5-year risk ( NRI = 0.31; standard error [ SE ] = 0.031) and IBIS remaining lifetime risk ( NRI = 0.287; SE = 0.035). Conclusion BRISK performs better than two commonly used clinical risk models and no worse compared to a similar model with more risk factors.