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Development and Validation of a Model for Predicting Diabetic Nephropathy in Chinese People.
Biomedical and Environmental Sciences : BES 2017 Februrary
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.
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.
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