Sex differences in impact of coronary artery calcification to predict coronary artery disease

Yoko M. Nakao, Yoshihiro Miyamoto, Masahiro Higashi, Teruo Noguchi, Mitsuru Ohishi, Isao Kubota, Hiroyuki Tsutsui, Tomohiro Kawasaki, Yutaka Furukawa, Michihiro Yoshimura, Hideaki Morita, Kunihiro Nishimura, Akiko Kada, Yoichi Goto, Tomonori Okamura, Chuwa Tei, Hitonobu Tomoike, Hiroaki Naito, Satoshi Yasuda

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1118-1124
Number of pages7
JournalHeart (British Cardiac Society)
Volume104
Issue number13
DOIs
Publication statusPublished - 2018 Jul 1

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Sex Characteristics
Coronary Artery Disease
Coronary Vessels
Coronary Angiography
Cohort Studies
Logistic Models
Atherosclerosis
Pathologic Constriction
Cardiovascular Diseases
Clinical Trials
Prospective Studies

Keywords

  • cardiac computer tomographic (ct) imaging
  • coronary artery disease

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

Nakao, Y. M., Miyamoto, Y., Higashi, M., Noguchi, T., Ohishi, M., Kubota, I., ... Yasuda, S. (2018). Sex differences in impact of coronary artery calcification to predict coronary artery disease. Heart (British Cardiac Society), 104(13), 1118-1124. https://doi.org/10.1136/heartjnl-2017-312151

Sex differences in impact of coronary artery calcification to predict coronary artery disease. / Nakao, Yoko M.; Miyamoto, Yoshihiro; Higashi, Masahiro; Noguchi, Teruo; Ohishi, Mitsuru; Kubota, Isao; Tsutsui, Hiroyuki; Kawasaki, Tomohiro; Furukawa, Yutaka; Yoshimura, Michihiro; Morita, Hideaki; Nishimura, Kunihiro; Kada, Akiko; Goto, Yoichi; Okamura, Tomonori; Tei, Chuwa; Tomoike, Hitonobu; Naito, Hiroaki; Yasuda, Satoshi.

In: Heart (British Cardiac Society), Vol. 104, No. 13, 01.07.2018, p. 1118-1124.

Research output: Contribution to journalArticle

Nakao, YM, Miyamoto, Y, Higashi, M, Noguchi, T, Ohishi, M, Kubota, I, Tsutsui, H, Kawasaki, T, Furukawa, Y, Yoshimura, M, Morita, H, Nishimura, K, Kada, A, Goto, Y, Okamura, T, Tei, C, Tomoike, H, Naito, H & Yasuda, S 2018, 'Sex differences in impact of coronary artery calcification to predict coronary artery disease', Heart (British Cardiac Society), vol. 104, no. 13, pp. 1118-1124. https://doi.org/10.1136/heartjnl-2017-312151
Nakao, Yoko M. ; Miyamoto, Yoshihiro ; Higashi, Masahiro ; Noguchi, Teruo ; Ohishi, Mitsuru ; Kubota, Isao ; Tsutsui, Hiroyuki ; Kawasaki, Tomohiro ; Furukawa, Yutaka ; Yoshimura, Michihiro ; Morita, Hideaki ; Nishimura, Kunihiro ; Kada, Akiko ; Goto, Yoichi ; Okamura, Tomonori ; Tei, Chuwa ; Tomoike, Hitonobu ; Naito, Hiroaki ; Yasuda, Satoshi. / Sex differences in impact of coronary artery calcification to predict coronary artery disease. In: Heart (British Cardiac Society). 2018 ; Vol. 104, No. 13. pp. 1118-1124.
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T1 - Sex differences in impact of coronary artery calcification to predict coronary artery disease

AU - Nakao, Yoko M.

AU - Miyamoto, Yoshihiro

AU - Higashi, Masahiro

AU - Noguchi, Teruo

AU - Ohishi, Mitsuru

AU - Kubota, Isao

AU - Tsutsui, Hiroyuki

AU - Kawasaki, Tomohiro

AU - Furukawa, Yutaka

AU - Yoshimura, Michihiro

AU - Morita, Hideaki

AU - Nishimura, Kunihiro

AU - Kada, Akiko

AU - Goto, Yoichi

AU - Okamura, Tomonori

AU - Tei, Chuwa

AU - Tomoike, Hitonobu

AU - Naito, Hiroaki

AU - Yasuda, Satoshi

PY - 2018/7/1

Y1 - 2018/7/1

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.

AB - 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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