A prediction model for type 2 diabetes risk among Chinese people

Abstract

Aims/hypothesis A range of prediction rules for the onset of type 2 diabetes have been proposed. However, most studies have been conducted in white groups and it is not clear whether these models apply to Asian populations. The purpose of this study was to construct a simple points model for predicting incident diabetes among Chinese people.Methods We estimated the 10 year risk of diabetes in a cohort study of middle-aged and elderly participants who were free from diabetes at baseline. Cox regression coefficients were used to construct the simple points model and the discriminatory ability of the resulting prediction rule was determined using AUC and net reclassification improvement and integrated discrimination improvement statistics. Fivefold random splitting was used to test the internal validity and obtain bootstrap estimates of the AUC. Results Of the 2,960 participants without diabetes at the baseline examination, 548 developed type 2 diabetes during a median 10 year follow-up period. Age (four points), elevated fasting glucose (11 points), body mass index (eight points), triacylglycerol (five points), white blood cell count (four points) and a higher HDL-cholesterol (negative four points) were found to strongly predict diabetes incidence in a multivariate model. The estimated AUC for the model was 0.702 (95% CI 0.676-0.727). This model performed better than existing prediction models developed in other populations, including the Prospective Cardiovascular Münster, Cambridge, San Antonia and Framingham models for diabetes risk. Conclusions/interpretation We have constructed a model for predicting the 10 year incidence of diabetes in Chinese people that could be useful for identifying individuals at high risk of diabetes in the Chinese population.

Prediction models for the risk of new-onset hypertension in ethnic Chinese in Taiwan

“…We constructed coefficient-based 24 and pointbased models 15,25 for predicting the risk of hypertension using the clinical and biochemical variables. With regard to the coefficient-based model, the risk scores were derived from the estimated coefficients and were calculated to absolute risk in the Weibull model.…”

“…Individuals with a fasting blood sugar level 4126 mg per 100 ml and/or use of oral hypoglycaemia agents or insulin injections were defined as diabetes mellitus. 15,23 …”

“…Second, we proposed two different scoring systems: regression coefficient-based scores 14 and point-based scores. 15 Finally, we tested the performance measures of these prediction models and compared the available models.…”

High-Density Lipoprotein-Cholesterol Trajectory Pattern, Associated Lifestyle and Biochemical Factors Among Taiwanese

“…33 In addition, the incidence of diabetes has increased substantially, 34 and obesity and inflammatory markers, such as white blood cell count, predict the risk of diabetes. 35 During the 4-year follow-up period, the body mass index changed significantly in both genders (P=0.001). Therefore, obesity control should be taken into consideration among the adult population, even over a short period.…”

Updated risk factors should be used to predict development of diabetes

“…Some have sought to improve prediction by adding additional genetic [4], laboratory [5,6], or clinical [7] parameters to the traditional sociodemographic risk factors of ethnicity, family history of diabetes, personal history of gestational diabetes, and physical inactivity. Comparatively little is known about the impact of change in common risk factors over time on risk prediction [8].…”