A nomogram of 5-year risk of type 2 diabetes in Chinese population

Objective: The aim of this study was to analyze the risk factors of type 2 diabetes in 5 years in Chinese population, and to construct the prediction model of nomogram and verify its validity. Methods: The physical examination and follow-up data of the participants who received physical examination at 32 sites in 11 cities in China from 2010 to 2016 were collected from the Dryad digital repository database. Randomly divided into modeling group (n = 22936) and validation group (n = 9830). In the modeling group, the independent risk factors were determined by single factor and multi factor analysis based on Cox regression model, and the nomogram prediction model was constructed by R software. The accuracy and performance of the model were evaluated by AUC value, C-index and calibration curve. Results: The multivariate regression model suggested that fasting blood glucose, triglyceride, smoking history and drinking history were independent risk predictors of 5-year risk of type 2 diabetes in Chinese population. In the modeling group, AUC was 0.776 (95%CI: 0.699-0.849), and C-index was 0.783 (95%CI: 0.706-0.856). Similarly, in the validation group, the AUC value was 0.743 (95%CI:0.665-0.824), and the C-index was 0.764 (95%CI: 0.667-0.846), suggesting that the model had a good discrimination ability. The 5-year adjusted risk curve of type 2 diabetes in Chinese population suggests a good consistency between the predicted value and the actual value. Conclusion: The nomogram model can predict the 5-year risk of type 2 diabetes in Chinese population intuitively and accurately.