Supplementary Material for: Developing a Stroke Risk Prediction Model Using Cardiovascular Risk Factors: The Suita Study

Introduction: Stroke remains a major cause of death and disability in Japan and worldwide. Detecting individuals at high risk for stroke to apply preventive approaches is recommended. This study aimed to develop a stroke risk prediction model among urban Japanese using cardiovascular risk factors. Methods: We followed 6,641 participants aged 30–79 years with neither a history of stroke nor coronary heart disease. The Cox proportional hazard model estimated the risk of stroke incidence adjusted for potential confounders at the baseline survey. The model’s performance was assessed using the receiver operating characteristic curve and the Hosmer-Lemeshow statistics. The internal validity of the risk model was tested using derivation and validation samples. Regression coefficients were used for score calculation. Results: During a median follow-up duration of 17.1 years, 372 participants developed stroke. A risk model including older age, current smoking, increased blood pressure, impaired fasting blood glucose and diabetes, chronic kidney disease, and atrial fibrillation predicted stroke incidence with an area under the curve = 0.76 and p value of the goodness of fit = 0.21. This risk model was shown to be internally valid (p value of the goodness of fit in the validation sample = 0.64). On a risk score from 0 to 26, the incidence of stroke for the categories 0–5, 6–7, 8–9, 10–11, 12–13, 14–15, and 16–26 was 1.1%, 2.1%, 5.4%, 8.2%, 9.0%, 13.5%, and 18.6%, respectively. Conclusion: We developed a new stroke risk model for the urban general population in Japan. Further research to determine the clinical practicality of this model is required.

前言：脑卒中（Stroke）仍是日本乃至全球范围内致死与致残的主要病因之一。学界推荐通过识别脑卒中高风险人群以开展针对性预防干预。本研究旨在利用心血管疾病风险因素，构建日本城市人群的脑卒中风险预测模型。
方法：本研究共纳入6641名年龄介于30至79岁之间、无脑卒中及冠心病病史的参与者进行队列随访。采用Cox比例风险模型（Cox proportional hazard model），校正基线调查中纳入的潜在混杂因素，估算脑卒中发病风险。通过受试者工作特征曲线（receiver operating characteristic curve, ROC曲线）与Hosmer-Lemeshow统计量评估模型性能。采用推导样本与验证样本检验该风险模型的内部有效性。以回归系数作为风险评分的计算依据。
结果：中位随访时长为17.1年，期间共有372名参与者发生脑卒中。纳入年龄增长、当前吸烟、血压升高、空腹血糖受损与糖尿病、慢性肾脏病（chronic kidney disease）以及心房颤动（atrial fibrillation）的风险模型，对脑卒中发病的预测效果显示曲线下面积（area under the curve, AUC）为0.76，拟合优度检验的P值为0.21。该风险模型被证实具有良好的内部有效性（验证样本的拟合优度检验P值为0.64）。在0至26分的风险评分体系下，0~5分、6~7分、8~9分、10~11分、12~13分、14~15分以及16~26分组的脑卒中发病率分别为1.1%、2.1%、5.4%、8.2%、9.0%、13.5%与18.6%。
结论：本研究成功构建了针对日本城市普通人群的新型脑卒中风险预测模型。未来仍需开展进一步研究以明确该模型的临床实用性。