The DOI matches its Crossref record; 56 of the 58 references it cites were found in a registry or an index.
Predicting Coronary Heart Disease Using Risk Factor Categories for a Japanese Urban Population, and Comparison with the Framingham Risk Score: The Suita Study
Open accessAbstract
AIM: The Framingham risk score (FRS) is one of the standard tools used to predict the incidence of coronary heart disease (CHD). No previous study has investigated its efficacy for a Japanese population cohort. The purpose of this study was to develop new coronary prediction algorithms for the Japanese population in the manner of the FRS, and to compare them with the original FRS. METHODS: Our coronary prediction algorithms for Japanese were based on a large population-based cohort study (Suita study). The study population comprised 5,521 healthy Japanese. They were followed-up for 11.8 years on average, and 213 cases of CHD were observed. Multiple Cox proportional hazard model by stepwise selection was used to construct the prediction model. RESULTS: Our coronary prediction algorithms for Japanese patients were based on a large populationbased cohort study (the Suita study). A multiple Cox proportional hazard model by stepwise selection was used to construct the prediction model. The C-statistics showed that the new model had better accuracy than the original and recalibrated Framingham scores. The net reclassification improvement (NRI) by the Suita score with the inclusion of CKD was 41.2% (P＜0.001) compared with the original FRS. The recalibration of the FRS slightly improved the efficiency of the prediction, but it was still worse than the Suita score with the CKD model. The calibration analysis suggested that the original FRS and the recalibrated FRS overestimated the risk of CHD in the Japanese population. The Suita score with CKD more accurately predicted the risk of CHD. CONCLUSION: The FRS and recalibrated FRS overestimated the 10-year risk of CHD for the Japanese population. A predictive score including CKD as a coronary risk factor for the Japanese population was more accurate for predicting CHD than the original Framingham risk scores in terms of the C-statics and NRI.
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“In terms of absolute risk, aging enhances the risk for ASCVD and death from it much more than any other risk factors160–162).”
From Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases 2017 (2018) · cites this paper as [161]
In the citing paper
“There are several assessment tool that predict the absolute risk of ASCVD in the Japanese population.”
From Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases 2017 (2018) · cites this paper as [161]
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Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization
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Prediction of coronary heart disease using risk factor categories
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Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers
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Items 201–225 of 225
Noguchi, T., Ota, H., Matsumoto, N., Morita, Y., Oshita, A., Kawasaki, E., Kawasaki, T., Moriwaki, K., Kato, S., Fukui, K., et al. (2022) · Trials · doi:10.1186/s13063-022-06820-w
“Study design This is a multicenter, parallel-group, prospective randomized controlled, open-label, superiority trial to assess the impact of non-contrast T1WI and CMRA on the diagnosis and management of patients at high risk for CAD estimated based on CAD risk factor categories for a Japanese urban population (Suita s…”
MethodSelf-citationUeki, H., Ohbayashi, M., Yamamoto, T., Inoue, T., & Kogo, M. (2022) · BPB Reports · doi:10.1248/bpbreports.5.6_125
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Impact of TKI Switching, Reduction, and Discontinuation on Cardiovascular Events in cml patientsPreprint
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Adachi, T., Ashikawa, H., Funaki, K., Kondo, T., & Yamada, S. (2023) · Journal of Occupational Health · doi:10.1093/joccuh/uiad011
“21 In addition to this basic model, logistic regression analysis was performed, adding age, sex, and BMI to calculate another PA score considering these variables (PA score 2).”
MethodKubozono, T. (2024) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.ed253
“The Suita score is an assessment tool used to predict the 10-year risk of developing cardiovascular heart disease (CHD) 3) ; the cutoff values of brachial–ankle vascular index (baPWV) are shown separately for age and gender using the Suita score 4) .”
MethodI. Revision of JAS Guidelines for Prevention of Atherosclerotic Cradiovascular Diseases in 2022
Okamura, T. (2023) · Nihon Naika Gakkai Zasshi · doi:10.2169/naika.112.157
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“The addition of CKD-specific variables such as kidney function and albuminuria to the FRS was suggested to improve the predictive value of the FRS in such patients [17 ], but some studies failed to show improvement in the predictive power of the FRS by adding CKD-specific variables [11 , 12 ].”
Okumiyama, H., Fujii, R., Tsuboi, Y., Murakami, K., Umematsu, R., Ando, Y., Ishikawa, H., Mizuno, G., Ohashi, K., Yamada, H., et al. (2025) · Journal of Epidemiology · doi:10.2188/jea.je20250292
Ogawa, A., Shoji‐Asahina, A., Kawaguchi, T., Nakayama, T., Matsuda, F., & Tabara, Y. (2025) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.65868
“The incidence rates of coronary artery events (including myocardial infarction, coronary artery bypass grafting, or angioplasty 25, 26) ) and stroke (including cerebral infarction and intracerebral and subarachnoid hemorrhage) were obtained from personal medical records stored at three emergency…”
Saigusa, T., Watanabe, K., Hada, Y., Ishii, K., Kameda, W., Susa, S., Ishizawa, K., & Ishihara, H. (2022) · Figshare · doi:10.6084/m9.figshare.20461911
Saigusa, T., Watanabe, K., Hada, Y., Ishii, K., Kameda, W., Susa, S., Ishizawa, K., & Ishihara, H. (2022) · Figshare · doi:10.6084/m9.figshare.20461908
Ichikawa, K., Miyoshi, T., Osawa, K., Nakashima, M., Takashi, M. I. K. I., Nishihara, T., Toda, H., Yoshida, M., & Ito, H. (2022) · Figshare · doi:10.6084/m9.figshare.19386847
Kobayashi, A., Terui, H., Shimada‐Omori, R., Okazaki, T., Sekine, M., Yano, M., Takahashi, T., & Asano, Y. (2026) · Immunological Medicine · doi:10.1080/25785826.2026.2641279
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“Using the Suita score [14], SCORE2 [15], and SCORE2-OP [16] risk charts, cardiovascular disease risk was evaluated, and 63 patients were classified into three risk categories: low (green), intermediate (yellow), and high (red).”
Lipids and Cardiovascular Diseases: Epidemiologic Perspectives
Nguyen, X.-M. T., Wilson, P. W. F., Okamura, T., Sugiyama, D., Hirata, T., Kuwabara, K., & Hirata, A. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-15734-9.00066-2
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“We used the Framingham risk score (Wilson et al., 1998) and the Suita risk score (Nishimura et al., 2014) to estimate each participant's 10-year risk of CHD.”
Major cardiovascular events in Japanese patients with acute and chronic coronary syndrome
Osada, N., Sheng, F., Chang, C.-H., Clouser, M., Tanaka, S., Ludwikowska, M., & Kohsaka, S. (2026) · Open Heart · doi:10.1136/openhrt-2026-004247
Cardiovascular Risk Assessment Chart by Dietary Factors in Japan - NIPPON DATA80.
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Self-citationMATSUMOTO, H., Kondo, K., Miura, K., Tanaka, S., 瀬川, 裕., 大野, 聖., Miyagawa, N., Okami, Y., 奥田, 奈., Nakagawa, H., et al. (2021) · Institutional Repositories DataBase (IRDB)
Self-citationRetinal Arterial Wall Reflectivity and Incident Cardiovascular Disease
Xiang, R., Muraoka, Y., Kogo, T., Hidaka, Y., Mori, Y., Hata, M., Miyake, M., Morita, S., Horie, T., Ono, K., et al. (2026) · Ophthalmology Science · doi:10.1016/j.xops.2026.101399
“In this large-scale longitudinal community-based cohort, retinal arterial wall reflectivity was not independently associated with incident CVD in the primary full-cohort multivariable analysis after adjustment for conventional cardiovascular risk factors, 22 baPWV, and CRAE.”
Ichikawa, T., Okada, H., Yamamoto, S., Sano, A., Hashimoto, Y., Kasahara, K., Nakajima, H., Hamaguchi, M., Murata, H., Kurogi, K., et al. (2026) · Diabetes Obesity and Metabolism · doi:10.1111/dom.71335
Tabara, Y., Murase, K., Matsumoto, T., Kawaguchi, T., Wakamura, T., Hirai, T., 陳, 和., & Matsuda, F. (2026) · American Journal of Hypertension · doi:10.1093/ajh/hpag124
Metadata
- Authors
- Nishimura, K., Okamura, T., Watanabe, M., Nakai, M., Takegami, M., Higashiyama, A., Kokubo, Y., Okayama, A., & Miyamoto, Y.
- Affiliations
- National Cerebral and Cardiovascular Center (JP)
- Keio University (JP)
- Hyogo Medical University (JP)
- Japan Anti Tuberculosis Association (JP)
- ORCID
- Venue
- Journal of Atherosclerosis and Thrombosis
- Publisher
- Japan Atherosclerosis Society
- Published
- 2014
- Volume
- 21
- Issue
- 8
- Pages
- 784-798
- ISSN
- 1340-3478 (ISSN-L)
- 1880-3873
- PMC
- PMC5090819
- OpenAlex
- W2043022783
- Cited by
- 228
- References
- 58
- Citations by year
- 2026: 10 · 2025: 13 · 2024: 25 · 2023: 25 · 2022: 34 · 2021: 33 · 2020: 20 · 2019: 19 · 2018: 20 · 2017: 10 · 2016: 12 · 2015: 4 · 2014: 2
- FWCI
- 9.29
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- Journal of Atherosclerosis and Thrombosis (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Cerebral and Cardiovascular Center (22-4-5)
- Japan Society for the Promotion of Science (25293147)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Keywords
- coronary artery disease, Framingham risk score, risk prediction model, Japanese population, chronic kidney disease, Suita Study, risk overestimation, net reclassification improvement, 10-year risk, urban population
- MeSH terms
- Adult, Aged, Algorithms, Coronary Disease, Female, Follow-Up Studies, Humans, Japan, Male, Middle Aged, Prognosis, Risk Factors, Urban Population, Cohort Studies, Biomarkers, Incidence, Proportional Hazards Models, Case-Control Studies, Risk Assessment
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