Cumulative Advanced Breast Cancer Risk Prediction Model Developed in a Screening Mammography Population
Abstract
BACKGROUND
Estimating advanced breast cancer risk in women undergoing annual or biennial mammography could identify women who may benefit from less or more intensive screening. We developed an actionable model to predict cumulative six-year advanced cancer (prognostic pathologic stage II or higher) risk according to screening interval.
METHODS
We included 931,186 women aged 40-74 years in the Breast Cancer Surveillance Consortium undergoing 2,542,382 annual (prior mammogram within 11-18 months) or 752,049 biennial (prior within 19-30 months) screening mammograms. The prediction model includes age, race/ethnicity, body mass index, breast density, family history of breast cancer, and prior breast biopsy subdivided by menopausal status and screening interval. We used 5-fold cross-validation to internally validate model performance. We defined >95th percentile as high-risk (>0.658%), >75th to <95th percentile as intermediate risk (0.380-0.658%), and <75th percentile as low to average risk (<0.380%).
RESULTS
Obesity, high breast density, and proliferative disease with atypia were strongly associated with advanced cancer. The model is well-calibrated and has an area under the receiver operating characteristics curve of 0.682 (95%CI 0.670-0.694). Based on women’s predicted advanced cancer risk under annual and biennial screening, 69.1% had low or average risk regardless of screening interval, 12.4% intermediate risk with biennial screening and average risk with annual screening, and 17.4% intermediate or high-risk regardless of screening interval.
CONCLUSIONS
Most women have low or average advanced cancer risk and can undergo biennial screening. Intermediate risk women may consider annual screening and high-risk women supplemental imaging in addition to annual screening.