Development of Risk Score for Predicting 3-Year Incidence of Type 2 Diabetes: Japan Epidemiology Collaboration on Occupational Health Study

Abstract

Objective: Risk models and scores have been developed to predict incidence of type 2 diabetes in Western populations, but their performance may differ when applied to non-Western populations. We developed and validated a risk score for predicting 3-year incidence of type 2 diabetes in a Japanese population.

Methods: Participants were 37,416 men and women, aged 30 or older, who received periodic health checkup in 2008-2009 in eight companies. Diabetes was defined as fasting plasma glucose (FPG) ≥ 126 mg/dl, random plasma glucose ≥ 200 mg/dl, glycated hemoglobin (HbA1c) ≥ 6.5%, or receiving medical treatment for diabetes. Risk scores on non-invasive and invasive models including FPG and HbA1c were developed using logistic regression in a derivation cohort and validated in the remaining cohort.

Results: The area under the curve (AUC) for the non-invasive model including age, sex, body mass index, waist circumference, hypertension, and smoking status was 0.717 (95% CI, 0.703-0.731). In the invasive model in which both FPG and HbA1c were added to the non-invasive model, AUC was increased to 0.893 (95% CI, 0.883-0.902). When the risk scores were applied to the validation cohort, AUCs (95% CI) for the non-invasive and invasive model were 0.734 (0.715-0.753) and 0.882 (0.868-0.895), respectively. Participants with a non-invasive score of ≥ 15 and invasive score of ≥ 19 were projected to have >20% and >50% risk, respectively, of developing type 2 diabetes within 3 years.

Conclusions: The simple risk score of the non-invasive model might be useful for predicting incident type 2 diabetes, and its predictive performance may be markedly improved by incorporating FPG and HbA1c.

Fig 1. Receiver operating characteristics (ROC) curves for each risk score model in predicting type 2 diabetes.

Abbreviation: FPG, fasting plasma glucose. In the delivation cohort, the area under the ROC (95% confidence interval) were 0.717 (0.703–0.731) for the non-invasive model, 0.843 (0.832–0.853) for the model including FPG, 0.827 (0.816–0.838) for the model including HbA1c, and 0.893 (0.883–0.902) for the model including both FPG and HbA1c. In the derivation cohort, the corresponding value were 0.734 (0.715–0.753) for the non-invasive model, 0.835 (0.820–0.851) for the model including FPG, 0.819 (0.803–0.835) for the model including HbA1c, and 0.882 (0.868–0.895) for the model including both FPG and HbA1c.

Fig 2. Observed and expected risk for developing type 2 diabetes (%) in each score of expected risk according to prediction models using the non-invasive model and the model including fasting plasma glucose and HbA1c in the derivation cohort; black bars, observed risk; grey bars, expected risk.