Adult ; Aged ; Area Under Curve ; Biomarkers/blood ; Body Mass Index ; Diabetes Mellitus/blood ; Diabetes Mellitus/diagnosis ; Diabetes Mellitus/epidemiology ; Diagnostic Self Evaluation ; Disease Progression ; Female ; Follow-Up Studies ; Humans ; Male ; Middle Aged ; Prognosis ; Proportional Hazards Models ; Prospective Studies ; ROC Curve ; Republic of Korea/epidemiology ; Risk
Abstract
To verify that the Korean Diabetes Score (KDS), a self-assessment, predicts the risk of diabetes in various comprehensive risk models, and to investigate factors that enhance its predictive ability in a large cohort. We analyzed 8735 adults without diabetes in the Korean Genome and Epidemiology Study, an ongoing large community-based 10-year cohort study. Incident diabetes was defined as fasting blood glucose ≥126 mg/dL or postload 2-hour glucose ≥200 mg/dL by 75 g oral glucose tolerance test conducted biennually, or currently taking medication for diabetes. Hazard ratios (HRs) using Cox regression were calculated for relative risk of developing diabetes as associated with the KDS, and performance of risk models was assessed by area under the receiver-operating characteristic curve (AUC). Of 8735 participants, 1497 (17.1%) developed diabetes over 10 years. The prevalence of incident diabetes was 10.3% in people with a KDS <5 and was 21.8% in those with KDS ≥5 (P < .001). Increasing KDS was significantly associated with developing diabetes (adjusted HR: 1.13; 95% confidence interval:1.09,1.18). The comprehensive prediction model with KDS added to fasting glucose, glycated hemoglobin, postload 2-hour glucose, and triglyceride showed a markedly higher AUC (0.782) compared to KDS alone (0.641). A low insulinogenic index (IGI) level, but not insulin resistance, was a significant determinant of developing diabetes in subjects who had baseline KDS < 5. We confirmed that KDS as a 10-year risk model to predict diabetes becomes more potent when added to relevant laboratory parameters. Beta-cell function as assessed by IGI should be taken into account when predicting diabetes using the KDS.