Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University.
Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University.
J Atheroscler Thromb. 2022 Mar 1;29(3):345-361. doi: 10.5551/jat.61960. Epub 2021 Jan 22.
To develop and validate a new risk prediction model for predicting the 10-year risk of atherosclerotic cardiovascular disease (ASCVD) in Japanese adults.
A total of 2,454 participants aged 40-84 years without a history of cardiovascular disease (CVD) were prospectively followed up for 24 years. An incident ASCVD event was defined as the first occurrence of coronary heart disease or atherothrombotic brain infarction. A Cox proportional hazards regression model was used to construct the prediction model. In addition, a simplified scoring system was translated from the developed prediction model. The model performance was evaluated using Harrell's C statistics, a calibration plot with the Greenwood-Nam-D'Agostino test, and a bootstrap validation procedure.
During a median of a 24-year follow-up, 270 participants experienced the first ASCVD event. The predictors of the ASCVD events in the multivariable Cox model included age, sex, systolic blood pressure, diabetes, serum high-density lipoprotein cholesterol, serum low-density lipoprotein cholesterol, proteinuria, smoking habits, and regular exercise. The developed models exhibited good discrimination with negligible evidence of overfitting (Harrell's C statistics: 0.786 for the multivariable model and 0.789 for the simplified score) and good calibrations (the Greenwood-Nam-D'Agostino test: P=0.29 for the multivariable model, 0.52 for the simplified score).
We constructed a risk prediction model for the development of ASCVD in Japanese adults. This prediction model exhibits great potential as a tool for predicting the risk of ASCVD in clinical practice by enabling the identification of specific risk factors for ASCVD in individual patients.
开发和验证一种新的风险预测模型，以预测日本成年人发生动脉粥样硬化性心血管疾病（ASCVD）的 10 年风险。
共前瞻性随访了 2454 名年龄在 40-84 岁、无心血管疾病（CVD）病史的参与者，随访时间为 24 年。ASCVD 事件的定义为首次发生冠心病或动脉粥样血栓性脑梗死。采用 Cox 比例风险回归模型构建预测模型。此外，还从开发的预测模型中翻译了一个简化的评分系统。采用 Harrell 的 C 统计量、Greenwood-Nam-D'Agostino 检验的校准图和 bootstrap 验证程序评估模型性能。
在中位数为 24 年的随访期间，270 名参与者发生了首次 ASCVD 事件。多变量 Cox 模型中 ASCVD 事件的预测因素包括年龄、性别、收缩压、糖尿病、血清高密度脂蛋白胆固醇、血清低密度脂蛋白胆固醇、蛋白尿、吸烟习惯和规律运动。开发的模型具有良好的区分度，几乎没有过度拟合的证据（Harrell 的 C 统计量：多变量模型为 0.786，简化评分模型为 0.789），且校准良好（Greenwood-Nam-D'Agostino 检验：多变量模型为 0.29，简化评分模型为 0.52）。
我们构建了一个日本成年人 ASCVD 发病风险的预测模型。该预测模型通过识别个体患者 ASCVD 的特定风险因素，有望成为临床实践中预测 ASCVD 风险的工具。
