Objective To develop a risk model for predicting later development of diabetic nephropathy （DN） in Chinese people with type 2 diabetes mellitus （T2DM） and evaluate its performance with independent validation. Meth...Objective To develop a risk model for predicting later development of diabetic nephropathy （DN） in Chinese people with type 2 diabetes mellitus （T2DM） and evaluate its performance with independent validation. Methods We used data collected from the project ＇Comprehensive Research on the Prevention and Control of Diabetes＇, which was a community-based study conducted by the Jiangsu Center for Disease Control and Prevention in 2013. A total of 11,771 eligible participants were included in our study. The endpoint was a clear diagnosis of DN. Data was divided into two components： a training set for model development and a test set for validation. The Cox proportional hazard regression was used for survival analysis in men and women. The model＇s performance was evaluated by discrimination and calibration. Results The incidence （cases per 10,000 person-years） of DN was 9.95 （95% CI; 8.66-11.43） in women and 11.28 （95% CI; 9.77-13.03） in men. Factors including diagnosis age, location, body mass index, high-density-lipoprotein cholesterol, creatinine, hypertension, dyslipidemia, retinopathy, diet control, and physical activity were significant in the final model. The model showed high discrimination and good calibration. Conclusion The risk model for predicting DN in people with T2DM can be used in clinical practice for improving the quality of risk management and intervention.展开更多
基金supported by grants from Jiangsu Provincial Medical Innovation Team Program[grant number K201105]Jiangsu Provincial Fourth‘333 Project’[grant number BRA2013107]
文摘Objective To develop a risk model for predicting later development of diabetic nephropathy （DN） in Chinese people with type 2 diabetes mellitus （T2DM） and evaluate its performance with independent validation. Methods We used data collected from the project ＇Comprehensive Research on the Prevention and Control of Diabetes＇, which was a community-based study conducted by the Jiangsu Center for Disease Control and Prevention in 2013. A total of 11,771 eligible participants were included in our study. The endpoint was a clear diagnosis of DN. Data was divided into two components： a training set for model development and a test set for validation. The Cox proportional hazard regression was used for survival analysis in men and women. The model＇s performance was evaluated by discrimination and calibration. Results The incidence （cases per 10,000 person-years） of DN was 9.95 （95% CI; 8.66-11.43） in women and 11.28 （95% CI; 9.77-13.03） in men. Factors including diagnosis age, location, body mass index, high-density-lipoprotein cholesterol, creatinine, hypertension, dyslipidemia, retinopathy, diet control, and physical activity were significant in the final model. The model showed high discrimination and good calibration. Conclusion The risk model for predicting DN in people with T2DM can be used in clinical practice for improving the quality of risk management and intervention.
