TY - JOUR T1 - Sex differences in impact of coronary artery calcification to predict coronary artery disease JF - Heart JO - Heart DO - 10.1136/heartjnl-2017-312151 SP - heartjnl-2017-312151 AU - Yoko M Nakao AU - Yoshihiro Miyamoto AU - Masahiro Higashi AU - Teruo Noguchi AU - Mitsuru Ohishi AU - Isao Kubota AU - Hiroyuki Tsutsui AU - Tomohiro Kawasaki AU - Yutaka Furukawa AU - Michihiro Yoshimura AU - Hideaki Morita AU - Kunihiro Nishimura AU - Akiko Kada AU - Yoichi Goto AU - Tomonori Okamura AU - Chuwa Tei AU - Hitonobu Tomoike AU - Hiroaki Naito AU - Satoshi Yasuda Y1 - 2018/01/13 UR - http://heart.bmj.com/content/early/2018/01/13/heartjnl-2017-312151.abstract N2 - 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. ER -