Prediction of 6-year incidence risk of chronic kidney disease in the elderly aged 65 years and older in 8 longevity areas in China
10.3760/cma.j.issn.0254-6450.2020.01.009
- VernacularTitle: 中国8个长寿地区65岁及以上老年人慢性肾脏病的6年发生风险预测
- Author:
Jinhui ZHOU
1
;
Yuan WEI
1
,
2
;
Yuebin LYU
1
;
Jun DUAN
1
,
3
;
Qi KANG
1
,
2
;
Jiaonan WANG
1
;
Wanying SHI
1
;
Zhaoxue YIN
4
;
Feng ZHAO
1
;
Yingli QU
1
;
Ling LIU
1
;
Yingchun LIU
1
;
Zhaojin CAO
1
;
Xiaoming SHI
1
Author Information
1. National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
2. Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China
3. Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei 230032, China
4. Division of Non-communicable Disease and Aging Health Management, Chinese Center for Disease Control and Prevention, Beijing 102206, China
- Publication Type:Journal Article
- Keywords:
Chronic kidney disease;
Incidence risk;
Prediction model;
Elderly
- From:
Chinese Journal of Epidemiology
2020;41(1):42-47
- CountryChina
- Language:Chinese
-
Abstract:
Objective: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.
Methods: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.
Results: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.
Conclusion: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.