Abstract PD4-06: A clinical model for assessing the individual breast cancer risk in mammography screening

Abstract

Abstract Background. Mammography screening reduces breast cancer mortality, but is suboptimal for the breast cancers that are not detected by the screening. These women are identified as symptomatic interval cancers with more aggressive tumors and worse pronosis. To efficiently screen for breast cancer the individual breast cancer risk should be determined. We describe a model that is suited for bi-annual screening programs and estimates the 2-year risk of breast cancer. The risk model could be used at most mammography screening units without adding substantial cost. Methods. The study was based on the population based prospective KARMA cohort including 70,877 participants. Mammograms were collected up to five years following baseline mammogram. A prediction model was developed using mammographic features (density, microcalcifications and masses), use of hormone replacement therapy (HRT), family history of breast cancer, menopausal status, and body mass index. Relative risks were calculated using conditional logistic regression and 2-year absolute risks were calculated Results. Comparing women at highest and lowest mammographic density yielded a 5-fold higher risk of breast cancer for women at highest density. When adding microcalcifications and masses to the model, high-risk women had a nearly 9-fold higher risk of breast cancer compared to those at lowest risk. In the full model, taking HRT use, family history of breast cancer and menopausal status into consideration, area under the curve (AUC) reached 0.73. We calculated the absolute 2-year risk of breast cancer based on national incidence and mortality rates. We also stratified women into risk groups using the NICE guidelines adapted to 2-year risks. The 20% women with moderate or high breast cancer risk were 7.6 times more likely to develop breast cancer compared to the general risk. Also 18% of the women showed 4 times reduced risk compared to the average population. Conclusions. This risk model can improve mammography screening by identifying women that are in need of additional examination procedures. There is also a substantial proportion of women with low breast cancer risk who will have little benefit from screening. Citation Format: Eriksson M, Czene K, Pawitan Y, Hall P. A clinical model for assessing the individual breast cancer risk in mammography screening [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD4-06.