Mikael Eriksson

Incorporating Continuous Mammographic Density Into the BOADICEA Breast Cancer Risk Prediction Model

PURPOSE Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA v7) predicts future breast cancer (BC) risk using data on cancer family history (FH), genetic markers, questionnaire-based risk factors, and mammographic density (MD) measured using the four-category Breast Imaging Reporting and Data System (BIRADS) classification. However, BIRADS requires manual reading, which is impractical on a large scale and may cause information loss. We extended BOADICEA to incorporate continuous MD measurements, calculated using the automated Volpara and STRATUS tools. METHODS We used data from the Karolinska Mammography Project for Risk Prediction of Breast Cancer cohort (60,276 participants; 1,167 incident BC). Associations between MD measurements and BC risk were estimated in a randomly selected training subset (two thirds of the data set). Percent MD residuals were calculated after regressing on age at mammography and BMI. Hazard ratios (HRs) were estimated using a Cox proportional hazards model, adjusting for FH and BOADICEA risk factors, and were incorporated into BOADICEA. The remaining one third of the cohort was used to assess the performance of the extended BOADICEA (v7.2) in predicting 5-year risks. RESULTS The BC HRs per standard deviation of residual STRATUS density were estimated to be 1.48 (95% CI, 1.33 to 1.64) and 1.41 (95% CI, 1.27 to 1.56) for pre- and postmenopausal women, respectively. The corresponding estimates for Volpara density were 1.27 (95% CI, 1.15 to 1.40) and 1.38 (95% CI, 1.25 to 1.54). The extended BOADICEA showed improved discrimination in the testing data set over using BIRADS, with a 1%-4% increase in AUC across different combinations of risk factors. On the basis of 5-year BC risk with MD as the sole input, approximately 11% of the women were reclassified into lower risk categories and 18% into higher risk categories using the extended model. CONCLUSION Incorporating continuous MD measurements into BOADICEA enhances BC risk stratification and facilitates the use of automated MD measures for risk prediction.

Breast Density Changes after Risk-Reducing Salpingo-oophorectomy in Women with a Pathogenic Germline Variant in BRCA1 or BRCA2

Abstract Background: We studied changes in mammographic density (MD) among premenopausal women with a pathogenic germline variant (PGV) in the BRCA1 or BRCA2 gene, comparing those who did and did not undergo risk-reducing salpingo-oophorectomy (RRSO) in the interval between mammograms, accounting for changes in exogenous oral contraceptive or hormone replacement therapy (HRT) use. Methods: From five studies of the International BRCA1/2 Carrier Cohort Study consortium, we included 691 participants who had two or more screening mammograms available, were less than 47 years at the time of RRSO (N = 208), or premenopausal at all mammograms without RRSO (N = 483). MD metrics [percent density (PD), dense area (DA), and non-DA] were quantified using STRATUS. Multivariable linear mixed models assessed changes in MD metrics between groups, adjusting for confounders. Results: The mean PD at first mammogram was 26.8% ± 15.3 (RRSO) and 31.3% ± 18.1 (no RRSO). In a median 1.1 years between mammograms, PD decreased on average by 0.9% [95% confidence interval (CI), −1.6 to −0.2] among women who did not undergo RRSO in the interval between mammograms compared with 5.9% (95% CI, −7.4 to −4.5) among women who underwent RRSO in the interval (adjusted difference, −5.9%; 95% CI, −9.5 to −2.2; P = 0.002). Results were driven primarily by MD changes among BRCA2 PGV carriers. The use of HRT after RRSO attenuated the decline in PD. Conclusions: On average, PD and DA decrease following RRSO in premenopausal carriers, particularly among BRCA2 PGV carriers. HRT formulation affects MD changes. Impact: A decrease in MD may inform the potential protective effect of RRSO against breast cancer.