Abstract P2-06-06: A clinical model for assessment of the individual breast cancer risk

Abstract Background. Most mammography screening programs are not individualized. To efficiently screen for breast cancer the individual risk of the disease should be determined. We describe a model that estimate the 2-year risk of breast cancer and 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 three years following baseline mammogram. A prediction protocol was developed using mammographic features (density, microcalcifications and masses), use of hormone replacement therapy (HRT), family history of breast cancer, menopausal status, age, and body mass index. Relative risks were calculated using conditional logistic regression. Absolute risks were calculated using the iCARE protocol. 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. The difference in microcalcifications and masses between left and right breast was a better predictor of breast cancer than number of microcalcifications and masses in the breasts. When calculating the absolute 2-year risk of breast cancer we stratified women using the NICE guidelines for 10-year risk divided by 5 (Table 1). The mean absolute 2-year risk of breast cancer in the different risk categories was 0.12%, 0.33%, 0.83% and 1.95% for women at low, moderate, general, and high risk. In most countries with established mammography screening programs approximately 5 women in a 1000 are diagnosed with breast cancer at regular screening. We managed to identify a low risk group of approximately 10% of all women where 1 woman in a 1000 will be diagnosed with breast cancer, contrasting the 2% of all women at highest risk where 20 women out of a 1000 will be diagnosed with breast cancer within 2 years of last negative screen (Table 1). In the full model, taking HRT use, family history of breast cancer and menopausal status into consideration, area under the curve (AUC) reached 0.71. Conclusions. Our model includes three mammographic features that could easily be derived from clinically available software. By adding information on some few established risk factors it is possible to improve clinical care by identifying women in need of additional examination procedures. At the same time there is a substantial proportion of women that will have very little benefit from mammography screening due to their low risk of breast cancer. Table 1. Absolute 2-year risk of breast cancer in women stratified in to risk categories based on the NICE guidelinesAbsolute 2-year risk (risk group)Percent women at riskMean absolute 2-year risk2Stratified 2-year risk0-0.15 (low)10.30.121.0 (reference)0.15-<0.6 (general)64.80.332.750.6-<1.6 (moderate)22.90.826.83≥1.6 (high)2.01.9516.2 Citation Format: Eriksson M, Czene K, Pawitan Y, Leifland K, Darabi H, Hall P. A clinical model for assessment of the individual breast cancer risk [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-06-06.