期刊
EUROPEAN RADIOLOGY
卷 30, 期 10, 页码 5417-5426出版社
SPRINGER
DOI: 10.1007/s00330-020-06901-x
关键词
Breast; Breast neoplasms; Breast density; Mammography; Risk assessment
资金
- Capital District Health Authority Research Fund
- Dalhousie University Radiology Research Foundation
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 < 0.001 and AUC = 0.664, p = 0.04, respectively). Adding the three remaining risk factors did not further improve performance (AUC = 0.665, p = 0.45). There was almost perfect agreement (kappa = 0.97) between risk assessments based on a classifier derived from image-derived risk factors, core biopsy, and family history compared with those derived from a model including all available risk factors. Conclusions Women in the general screening population can be risk-stratified at time of screen using a simple model based on age, PMD, breast volume, and biopsy and family history.
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