Development of new diabetes risk scores on the basis of the current definition of diabetes in Japanese subjects [Rapid Communication]

Abstract

Abstract. To develop diabetes risk score (RS) based on the current definition of diabetes, we retrospectively analyzed consecutive 4,159 health examinees who were non-diabetic at baseline. Diabetes, diagnosed by fasting plasma glucose (FPG) ≥7.0 mmol/L, 2hPG ≥11.1 mmol/L and/or HbA1c ≥6.5% (48 mmol/mol), developed in 279 of them during the mean period of 4.9 years. A full RS (RS Full ), a RS without 2hPG (RS -2hPG ) and a non-invasive RS (RS NI ) were created on the basis of multivariate Cox proportional model by weighted grading based on hazard ratio in half the persons assigned. The RSs were verified in the remaining half of the participants. Positive family history (FH), male sex, smoking and higher age, systolic blood pressure (SBP), FPG, 2hPG and HbA1c were independent predictors for RS Full . For RS -2hPG , 7 independent predictors, exclusive of 2hPG and smoking but inclusive of elevated triglycerides (TG) comparing to RS Full , were selected. FH, male sex, and higher age, SBP and HbA1c were independent predictors in RS NI . In the validation cohort, C-statistic (95%CI) of RS Full , RS -2hPG and RS NI were 0.80 (0.76-0.84), 0.75 (0.70-0.78) and 0.68 (0.63-0.72), respectively, which were significantly different from each other (P <0.01). Absolute percentage difference between predicted probability and observed diabetes were 1.9%, 0.7% and 0.9%, by the three scores, respectively, and not significantly different from each other. In conclusion, diabetes defined by the current criteria was predicted by the new diabetes risk scores with reasonable accuracy. Nonetheless, RS Full with a postchallenge glucose value performed superior to RS -2hPG and RS NI .

Development and validation of risk models to predict the 7‐year risk of type 2 diabetes: The Japan Epidemiology Collaboration on Occupational Health Study

“…The non‐invasive prediction model showed fair predictive ability, with an AUROC of 0.73, which was within the reported range based on previous studies carried out in Japan (AUROC ranged between 0.68 and 0.77) and other countries (AUROC ranged between 0.62 and 0.87). As expected, our invasive model including both HbA1c and FPG showed a convincing performance for predicting diabetes.…”

“…However, these risk models might not be applied to external populations, particularly if ethnicities and countries differ from the derivation populations. In Japan, a few risk models have been developed using data from health checkups at hospital or local community settings. Among these, some were developed utilizing a small sample ( n < 2,000), and excluded individuals aged >40 years.…”

“…Among these, some were developed utilizing a small sample ( n < 2,000), and excluded individuals aged >40 years. Furthermore, some models included variables that were not routinely collected at regular health checkups (e.g., family health history and exercise), limiting the wider use of these prediction tools.…”

Diabetes prevention in the real world: Insights from the JDPP and J‐DOIT1

“…A cost‐effective approach is needed to achieve T2D prevention in routine primary care and the general population. Family histories of T2D, metabolic syndrome (MetS), and nonalcoholic fatty liver disease (NAFLD) are also associated with an increased risk of T2D . It is unclear whether MetS and NAFLD are associated with an increased risk of T2D.…”

“…Family histories of T2D, metabolic syndrome (MetS), and nonalcoholic fatty liver disease (NAFLD) are also associated with an increased risk of T2D. [38][39][40] It is unclear whether MetS and NAFLD are associated with an increased risk of T2D. From the point of view of a cost-effective approach, possible target population and target values are summarized in Table 5.…”