Scoring model to predict risk of chronic kidney disease in Chinese health screening examinees with type 2 diabetes

Abstract

Purpose: As health screening continues to increase in China, there is an opportunity to integrate a large number of demographic as well as subjective and objective clinical data into risk prediction modeling. The aim of this study was to develop and validate a prediction model for chronic kidney disease (CKD) in Chinese health screening examinees with type 2 diabetes mellitus (T2DM). Methods: We conducted a retrospective cohort study consisting of 2051 Chinese T2DM patients between 35 and 78 years old who were enrolled in the XY3CKD Follow-up Program between 2009 and 2010. All participants were randomly assigned into a derivation set or a validation set at a 2:1 ratio. Cox proportional hazards regression model was selected for the analysis of risk factors for the development of the proposed risk model of CKD. We established a prediction model with a scoring system following the steps proposed by the Framingham Heart Study. Results: The mean follow-up was 8.52 years, with a total of 315 (23.20%) and 189 (27.27%) incident CKD cases in the derivation set and validation set, respectively. We identified the following risk factors: age, gender, body mass index, duration of type 2 diabetes, variation of fasting blood glucose, stroke, and hypertension. The points were summed to obtain individual scores (from 0 to 15). The areas under the curve of 3-, 5- and 10-year CKD risks were 0.843, 0.799 and 0.780 in the derivation set and 0.871, 0.803 and 0.785 in the validation set, respectively. Conclusions: The proposed scoring system is a promising tool for further application of assisting Chinese medical staff for early prevention of T2DM complications among health screening examinees.