Development and validation of a cardiovascular risk prediction model for Japanese: The Hisayama study

Hisatomi Arima, Koji Yonemoto, Yasufumi Doi, Toshiharu Ninomiya, Jun Hata, Yumihiro Tanizaki, Masayo Fukuhara, Kiyoshi Matsumura, Mitsuo Iida, Yutaka Kiyohara

研究成果: Contribution to journalArticle査読

32 被引用数 (Scopus)

抄録

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, n1756) 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, n878). 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-statistic0.81; 95% confidence interval, 0.77 to 0.86) and calibration (Hosmer-Lemeshow 2-statistic6.46; P0.60). 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.

本文言語英語
ページ(範囲)1119-1122
ページ数4
ジャーナルHypertension Research
32
12
DOI
出版ステータス出版済み - 12 23 2009

All Science Journal Classification (ASJC) codes

  • 内科学
  • 生理学
  • 循環器および心血管医学

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