Risk Models to Predict Screen-Detected and Interval Breast Cancers in Population Mammography Screening Participants.

AIM

The aim of this study was to determine whether women at risk of having screen-detected (including detected at advanced stage) and interval breast cancer can be accurately identified using conventional risk factors collected by national screening programs.

METHODS

All 1,026,137 mammography screening examinations for 323,082 women attending the BreastScreen Western Australia program (part of Australia's national biennial screening program) in July 2007-June 2017 contributed to models for predicting screen-detected breast cancers, screen-detected advanced cancers (≥pT2), and interval cancers.

RESULTS

In total, 7024 screen-detected (1551 in situ, 5472 invasive, of which 1329 were ≥pT2) and 1866 interval cancers (76 in situ, 1790 invasive) were diagnosed. In a multivariable model for screen-detected cancers, the ORs for the oldest age groups were 2.56 (CI 2.32-2.82) for 60-69 years and 3.60 (CI 3.23-4.00) for ≥70 years, and the OR for symptoms was 7.44 (CI 6.76-8.20). These associations were stronger for screen-detected advanced cancers. First-degree family history and a personal history of breast cancer were also associated with risk. In a multivariable model for interval cancers, the HR for dense breasts was 2.36 (CI 2.14-2.61) and the HR for symptoms was 3.27 (CI 2.53-4.24); family history and recent hormone replacement therapy use were also associated with risk. The areas under the receiver operating characteristic curves were 0.643 (CI 0.636-0.650) for screen-detected cancers, 0.651 (CI 0.638-0.664) for screen-detected advanced cancers, and 0.706 (CI 0.690-0.722) for interval cancers.

CONCLUSION

Older age and symptoms were the strongest predictors of overall and advanced screen-detected breast cancers. Dense breasts and symptoms were the strongest predictors of interval cancers. All models had moderate discrimination, approximating that for established models.