Two risk score models for predicting incident Type 2 diabetes in Japan

Area of Science:

• Endocrinology
• Public Health
• Epidemiology

Background:

• Risk scoring models are crucial for identifying individuals at high risk of Type 2 diabetes mellitus.
• Established risk scoring approaches for Type 2 diabetes are lacking in the Japanese population.

Purpose of the Study:

• To develop and validate practical risk score models for predicting incident Type 2 diabetes in the Japanese population.
• To enable early identification of high-risk individuals without requiring an oral glucose tolerance test.

Main Methods:

• A derivation cohort (n=1935) was followed for 14 years, and a validation cohort (n=1147) for 5 years.
• Cox proportional hazards models were used to estimate risk scores based on significant factors like age, sex, BMI, and hypertension.
• Two models were developed: a non-invasive model and a model including fasting plasma glucose.

Main Results:

• The non-invasive model achieved an Area Under the Curve (AUC) of 0.700, while the plus-fasting plasma glucose model achieved an AUC of 0.772.
• Both models demonstrated significant predictive ability for Type 2 diabetes in the validation cohort, with increasing cumulative incidence correlating with higher risk scores.
• The plus-fasting plasma glucose model showed superior predictive performance compared to impaired glucose tolerance assessment.

Conclusions:

• Two practical risk score models were successfully developed for the Japanese population.
• These models facilitate the identification of individuals at high risk for Type 2 diabetes.
• The developed models offer a convenient alternative to oral glucose tolerance tests for risk assessment.