Zhou J H, Wei Y, Lyu Y B, Duan J, Kang Q, Wang J N, Shi W Y, Yin Z X, Zhao F, Qu Y L, Liu L, Liu Y C, Cao Z J, Shi X M
National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2020 Jan 10;41(1):42-47. doi: 10.3760/cma.j.issn.0254-6450.2020.01.009.
To establish a prediction model for 6-year incidence risk of chronic kidney disease (CKD) in the elderly aged 65 years and older in China. In this prospective cohort study, we used the data of 3 742 participants collected during 2008/2009-2014 and during 2012-2017/2018 from Healthy Aging and Biomarkers Cohort Study, a sub-cohort of the Chinese Longitudinal Healthy Longevity Survey. Two follow up surveys for renal function were successfully conducted for 1 055 participants without CKD in baseline survey. Lasso method was used for the selection of risk factors. The risk prediction model of CKD was established by using Cox proportional hazards regression models and visualized through nomogram tool. Bootstrap method (1 000 resample) was used for internal validation, and the performance of the model was assessed by C-index and calibration curve. The mean age of participants was (80.8±11.4) years. In 4 797 person years of follow up, CKD was found in 262 participants (24.8). Age, BMI, sex, education level, marital status, having retirement pension or insurance, hypertension prevalence, blood uric acid, blood urea nitrogen and total cholesterol levels and estimated glomerular filtration rate in baseline survey were used in the model to predict the 6-year incidence risk of CKD in the elderly. The corrected C-index was 0.766, the calibration curve showed good consistence between predicted probability and observed probability in high risk group, but relatively poor consistence in low risk group. The incidence risk prediction model of CKD established in this study has a good performance, and the nomogram can be used as visualization tool to predict the 6-year risk of CKD in the elderly aged 65 years and older in China.
建立中国65岁及以上老年人慢性肾脏病(CKD)6年发病风险的预测模型。在这项前瞻性队列研究中,我们使用了来自中国健康与生物标志物队列研究(中国纵向健康长寿调查的一个子队列)在2008/2009 - 2014年以及2012 - 2017/2018年期间收集的3742名参与者的数据。对基线调查中1055名无CKD的参与者成功进行了两次肾功能随访调查。采用Lasso方法进行危险因素选择。使用Cox比例风险回归模型建立CKD风险预测模型,并通过列线图工具进行可视化。采用Bootstrap方法(1000次重采样)进行内部验证,并通过C指数和校准曲线评估模型性能。参与者的平均年龄为(80.8±11.4)岁。在4797人年的随访中,262名参与者(24.8%)被发现患有CKD。模型中使用了年龄、体重指数、性别、教育水平、婚姻状况、是否有退休养老金或保险、高血压患病率、血尿酸、血尿素氮和总胆固醇水平以及基线调查中的估计肾小球滤过率来预测老年人CKD的6年发病风险。校正后的C指数为0.766,校准曲线显示高风险组预测概率与观察概率之间一致性良好,但低风险组一致性相对较差。本研究建立的CKD发病风险预测模型性能良好,列线图可作为可视化工具预测中国65岁及以上老年人CKD的6年风险。