A Novel Breast Arterial Calcification Age-Based Percentile Nomogram for the Incremental Prediction of Incidental Cardiovascular Events

BACKGROUND: Breast arterial calcification (BAC) detected on routine mammography is an emerging marker of cardiovascular risk in women. However, substantial age-related variability limits its clinical interpretability. Age-adjusted nomograms may improve risk stratification and communication. OBJECTIVES: This study aims to determine whether age-adjusted BAC percentiles derived from mammography predict major adverse cardiovascular events (MACE) independent of atherosclerotic cardiovascular disease (ASCVD) risk scores. METHODS: In this multicenter retrospective cohort study, 21,514 women without known cardiovascular disease and aged ≥40 years (57 ± 12 years) from sites in the United States and Australia underwent screening mammography and ASCVD risk assessment. BAC was quantified using artificial intelligence (cmAngio research edition, CureMetrix Inc) and expressed as age-adjusted percentiles. The primary outcome was MACE (death, ischemic heart disease, stroke, or heart failure). Associations between BAC percentiles with MACE were adjusted for established cardiovascular risk factors using Cox and competing risk regression methods, and incremental predictive value was evaluated. RESULTS: BAC was present in 22.7% of women, increasing with age (8%: <50 years; 61%: >70 years). During a mean follow-up of 4.7 years, 828 MACE (3.8%) occurred. Each 10-percentile increase in BAC was associated with a 17% relative increase in MACE risk (adjusted HR [aHR]: 1.17 [95% CI: 1.015-1.019]; P < 0.001), independent of conventional risk factors. Associations remained significant for each MACE component in competing risk models (all P < 0.001). Women with low ASCVD risk (80% of cohort) had significantly increased MACE with both BAC percentile less than median (aHR: 1.66 [95% CI: 1.35-2.04], P < 0.001) and more than median (aHR: 2.31 [95% CI: 1.82-2.93], P < 0.001). Women with intermediate and high ASCVD risk had greater MACE when BAC was more than median (intermediate aHR: 1.40 [95% CI: 1.07-1.82], P = 0.01; high aHR: 1.65 [95% CI: 1.24-2.21], P < 0.001). The addition of BAC to ASCVD risk score appropriately up-classified 9% of individuals with MACE and down-classified 3% of individuals without events, resulting in an overall net reclassification index of 5% ± 1%. The C-statistic for the clinical model improved from 0.67 to 0.71 (Δ 0.04 [95% CI: 0.01-0.07]; P = 0.042) with addition of BAC. CONCLUSIONS: Age-adjusted BAC independently predicts cardiovascular events beyond traditional ASCVD risk scores and reclassifies low- and intermediate-risk individuals. Integration of BAC into cardiovascular risk assessment frameworks may facilitate early identification of at-risk women.