Key result
Adding CAC score to clinical factors improves obstructive CAD detection, linked to ~79% higher odds per log-unit.
Why the study?
Sex-specific differences in the predictive ability of coronary artery calcification (CAC) combined with conventional risk factors for detecting coronary artery disease (CAD) were not well characterized.
Cross-Sectional (n=991)
Single-blind (radiologist blinded to clinical data)
Yes
Odds Ratio: 1.79 (95% CI 1.56–2.06)
p-value: p=<0.001
May improve obstructive CAD risk classification when added to clinical factors; leaves open prospective validation and sex-specific thresholds.
OBJECTIVE: To assess sex-specific differences regarding use of conventional risks and coronary artery calcification (CAC) to detect coronary artery disease (CAD) using coronary CT angiography (CCTA). METHODS: The Nationwide Gender-specific Atherosclerosis Determinants Estimation and Ischemic Cardiovascular Disease Prospective Cohort study is a prospective, multicentre, nationwide cohort study. Candidates with suspected CAD aged 50-74 years enrolled from 2008 to 2012. The outcome was obstructive CAD defined as any stenosis ≥50% by CCTA. We constructed logistic regression models for obstructive CAD adjusted for conventional risks (clinical model) and CAC score. Improvement in discrimination beyond risks was assessed by C-statistic; net reclassification index (NRI) for CAD probability of low (<30%), intermediate (30%-60%) and high (≥60%); and risk stratification capacity. RESULTS: Among 991 patients (456 women, 535 men; 65.2 vs 64.4 years old), women had lower CAC scores (median, 4 vs 60) and lower CAD prevalence (21.7% vs 37.0%) than men. CAC significantly improved model discrimination compared with clinical model in both sexes (0.66-0.79 in women vs 0.61-0.83 in men). The NRI for women was 0.33, which was much lower than that for men (0.71). Adding CAC to clinical model had a larger benefit in terms of moving an additional 43.3% of men to the most determinant categories (high or low risk) compared with -1.4% of women. CONCLUSIONS: The addition of CAC to a prediction model based on conventional variables significantly improved the classification of risk in suspected patients with CAD, with sex differences influencing the predictive ability. TRIAL REGISTRATION NUMBER: UMIN-CTR Clinical Trial: UMIN000001577.
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Nakao et al. (2018) conducted a cross-sectional in Suspected coronary artery disease (n=991). Coronary artery calcification (CAC) score vs. Conventional risk factors alone (clinical model) was evaluated on Obstructive CAD (≥50% stenosis by CCTA) detection in men (per log-unit CAC score) (OR 1.79, 95% CI 1.56-2.06, p=<0.001). Adding the coronary artery calcification score to conventional clinical risk factors significantly improved the detection and risk classification of obstructive coronary artery disease in both sexes, though men demonstrated a substantially higher net reclassification index (0.71) than women (0.33).
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