Assessing breast cancer risk within the general screening population: developing a breast cancer risk model to identify higher risk women at mammographic screening

Objectives To develop a breast cancer risk model to identify women at mammographic screening who are at higher risk of breast cancer within the general screening population. Methods This retrospective nested case-control study used data from a population-based breast screening program (2009–2015). All women aged 40–75 diagnosed with screen-detected or interval breast cancer ( n = 1882) were frequency-matched 3:1 on age and screen-year with women without screen-detected breast cancer ( n = 5888). Image-derived risk factors from the screening mammogram (percent mammographic density [PMD], breast volume, age) were combined with core biopsy history, first-degree family history, and other clinical risk factors in risk models. Model performance was assessed using the area under the receiver operating characteristic curve (AUC). Classifiers assigning women to low- versus high-risk deciles were derived from risk models. Agreement between classifiers was assessed using a weighted kappa. Results The AUC was 0.597 for a risk model including only image-derived risk factors. The successive addition of core biopsy and family history significantly improved performance (AUC = 0.660, p