Development and validation of a cardiovascular risk prediction model for Japanese: the Hisayama study
Open accessAbstract
The objective of this paper is to develop a new risk prediction model of cardiovascular disease and to validate its performance in a general population of Japanese. The Hisayama study is a population-based prospective cohort study. A total of 2634 participants aged 40 years or older were followed up for 14 years for incident cardiovascular disease (stroke and coronary heart disease (myocardial infarction, coronary revascularization and sudden cardiac death)). We used data among a random two-thirds (the derivation cohort, n=1756) to develop a new risk prediction model that was then tested to compare observed and predicted outcomes in the remaining one-third (the validation cohort, n=878). A multivariable cardiovascular risk prediction model was developed that incorporated age, sex, systolic blood pressure, diabetes, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and smoking. We assessed the performance of the model for predicting individual cardiovascular event among the validation cohort. The risk prediction model demonstrated good discrimination (c-statistic=0.81; 95% confidence interval, 0.77 to 0.86) and calibration (Hosmer-Lemeshow chi(2)-statistic=6.46; P=0.60). A simple risk score sheet based on the cardiovascular risk prediction model was also presented. We developed and validated a new cardiovascular risk prediction model in a general population of Japanese. The risk prediction model would provide a useful guide to estimate absolute risk of cardiovascular disease and to treat individual risk factors.
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This model predicts cerebro-cardiovascular disease incidence including stroke and CAD within 10 years.
“Not like the Framingham Score which predicts only CAD incidence, this model predicts cerebro-cardiovascular disease incidence including stroke and CAD within 10 years.”
From Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases 2017 (2018) · cites this paper as [333]
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- Authors
- Arima, H., Yonemoto, K., Doi, Y., Ninomiya, T., Hata, J., Tanizaki, Y., Fukuhara, M., Matsumura, K., Iida, M., & Kiyohara, Y.
- Affiliations
- Kyushu University (JP)
- Corresponding author
- Arima, Hisatomi
- Venue
- Hypertension Research
- Published
- 2009-09-18
- Volume
- 32
- Issue
- 12
- Pages
- 1119-1122
- ISSN
- 0916-9636 (ISSN-L)
- 1348-4214
- OpenAlex
- W1985719600
- Cited by
- 66
- References
- 25
- Citations by year
- 2026: 6 · 2025: 3 · 2024: 3 · 2023: 5 · 2022: 6 · 2021: 6 · 2020: 4 · 2019: 7 · 2018: 4 · 2017: 5 · 2016: 3 · 2015: 3 · 2014: 2 · 2013: 3 · 2012: 1
- FWCI
- 2.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Hypertension Research (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Japan Society for the Promotion of Science (19590633, 18209024, 21590698)
- 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 › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- cardiovascular risk prediction models, Hisayama Study, Japanese population, stroke, coronary artery disease, myocardial infarction, coronary revascularization, sudden cardiac death, risk score, systolic blood pressure, diabetes mellitus, LDL cholesterol, HDL cholesterol, smoking, absolute risk estimation, model validation
- MeSH terms
- Adult, Aged, Cardiovascular Diseases, Female, Humans, Japan, Male, Middle Aged, Predictive Value of Tests, Prospective Studies, Risk Factors, Reproducibility of Results, Models, Statistical, Cohort Studies, Risk Assessment, Asian People
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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