Risk prediction models for type 2 diabetes using either fasting plasma glucose or HbA1c in Chinese, Malay, and Indians: Results from three multi-ethnic Singapore cohorts

Aims: To assess three well-established type 2 diabetes (T2D) risk prediction models based on fasting plasma glucose (FPG) in Chinese, Malays, and Indians, and to develop simplified risk models based on either FPG or HbA1c. Methods: We used a prospective multiethnic Singapore cohort to evaluate the established models and develop simplified models. 6,217 participants without T2D at baseline were included, with an average follow-up duration of 8.3 years. The simplified risk models were validated in two independent multiethnic Singapore cohorts (N = 12,720). Results: The established risk models had moderate-to-good discrimination (area under the receiver operating characteristic curves, AUCs 0.762 - 0.828) but a lack of fit (P-values < 0.05). Simplified risk models that included fewer predictors (age, BMI, systolic blood pressure, triglycerides, and HbA1c or FPG) showed good discrimination in all cohorts (AUCs >= 0.810), and sufficiently captured differences between the ethnic groups. While recalibration improved fit the simplified models in validation cohorts, there remained evidence of miscalibration in Chinese (p <= 0.012). Conclusions: Simplified risk models including HbA1c or FPG had good discrimination in predicting incidence of T2D in three major Asian ethnic groups. Risk functions with HbA1c performed as well as those with FPG.

Automated summary

This study assessed the performance of three well-established type 2 diabetes risk prediction models based on fasting plasma glucose (FPG) in Chinese, Malays, and Indians, and developed simplified risk models based on either FPG or HbA1c. The simplified risk models showed good discrimination in all ethnic groups and effectively captured the differences between them.