OBJECTIVES: This study sought to determine if breast arterial calcification (BAC) on digital mammography predicts coronary artery calcification (CAC). BACKGROUND: BAC is frequently noted but the quantitative relationships to CAC and risk factors are unknown. METHODS: A total of 292 women with digital mammography and nongated computed tomography was evaluated. BAC was quantitatively evaluated (0 to 12) and CAC was measured on computed tomography using a 0 to 12 score; they were correlated with each other and the Framingham Risk Score (FRS) and the 2013 Cholesterol Guidelines Pooled Cohort Equations (PCE). RESULTS: BAC was noted in 42.5% and was associated with increasing age (p < 0.0001), hypertension (p = 0.0007), and chronic kidney disease (p < 0.0001). The sensitivity, specificity, positive and negative predictive values, and accuracy of BAC >0 for CAC >0 were 63%, 76%, 70%, 69%, and 70%, respectively. All BAC variables were predictive of the CAC score (p < 0.0001). The multivariable odds ratio for CAC >0 was 3.2 for BAC 4 to 12, 2.0 for age, and 2.2 for hypertension. The agreements of FRS risk categories with CAC and BAC risk categories were 57% for CAC and 55% for BAC; the agreement was 47% for PCE risk categories for CAC and 54% by BAC. BAC >0 had area under the curve of 0.73 for identification of women with CAC >0, equivalent to both FRS (0.72) and PCE (0.71). BAC >0 increased the area under the curve curves for FRS (0.72 to 0.77; p = 0.15) and PCE (0.71 to 0.76; p = 0.11) for the identification of high-risk (4 to 12) CAC. With the inclusion of 33 women with established CAD, BAC >0 was significantly additive to both FRS (p = 0.02) and PCE (p = 0.04) for high-risk CAC. CONCLUSIONS: There is a strong quantitative association of BAC with CAC. BAC is superior to standard cardiovascular risk factors. BAC is equivalent to both the FRS and PCE for the identification of high-risk women and is additive when women with established CAD are included.
OBJECTIVES: This study sought to determine if breast arterial calcification (BAC) on digital mammography predicts coronary artery calcification (CAC). BACKGROUND: BAC is frequently noted but the quantitative relationships to CAC and risk factors are unknown. METHODS: A total of 292 women with digital mammography and nongated computed tomography was evaluated. BAC was quantitatively evaluated (0 to 12) and CAC was measured on computed tomography using a 0 to 12 score; they were correlated with each other and the Framingham Risk Score (FRS) and the 2013 Cholesterol Guidelines Pooled Cohort Equations (PCE). RESULTS: BAC was noted in 42.5% and was associated with increasing age (p < 0.0001), hypertension (p = 0.0007), and chronic kidney disease (p < 0.0001). The sensitivity, specificity, positive and negative predictive values, and accuracy of BAC >0 for CAC >0 were 63%, 76%, 70%, 69%, and 70%, respectively. All BAC variables were predictive of the CAC score (p < 0.0001). The multivariable odds ratio for CAC >0 was 3.2 for BAC 4 to 12, 2.0 for age, and 2.2 for hypertension. The agreements of FRS risk categories with CAC and BAC risk categories were 57% for CAC and 55% for BAC; the agreement was 47% for PCE risk categories for CAC and 54% by BAC. BAC >0 had area under the curve of 0.73 for identification of women with CAC >0, equivalent to both FRS (0.72) and PCE (0.71). BAC >0 increased the area under the curve curves for FRS (0.72 to 0.77; p = 0.15) and PCE (0.71 to 0.76; p = 0.11) for the identification of high-risk (4 to 12) CAC. With the inclusion of 33 women with established CAD, BAC >0 was significantly additive to both FRS (p = 0.02) and PCE (p = 0.04) for high-risk CAC. CONCLUSIONS: There is a strong quantitative association of BAC with CAC. BAC is superior to standard cardiovascular risk factors. BAC is equivalent to both the FRS and PCE for the identification of high-risk women and is additive when women with established CAD are included.
Authors: Eva J E Hendriks; Joline W J Beulens; Pim A de Jong; Yvonne T van der Schouw; Wei-Ning Sun; C Michael Wright; Michael H Criqui; Matthew A Allison; Joachim H Ix Journal: Atherosclerosis Date: 2017-01-30 Impact factor: 5.162
Authors: Morgan Lamberg; Andrea Rossman; Alexandra Bennett; Sabrina Painter; Rachel Goodman; James MacLeod; Ragasnehith Maddula; David Rayan; Krishna Doshi; Alexander Bick; Simone Bailey; Sherry-Ann Brown Journal: Curr Atheroscler Rep Date: 2022-04-19 Impact factor: 5.113