Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models.

INTRODUCTION

Insulin resistance and defects in pancreatic beta cells are the two major pathophysiologic abnormalities that underlie type 2 diabetes. In addition, visceral fat area (VFA) is reported to be a stronger predictor for diabetes than body mass index (BMI). Here, we tested whether the performance of diabetes prediction models could be improved by adding HOMA-IR and HOMA-β and replacing BMI with VFA.

RESEARCH DESIGN AND

METHODS

We developed five prediction models using data from a cohort study (5578 individuals, of whom 94.7% were male, and 943 had incident diabetes). We conducted a baseline model (model 1) including age, sex, BMI, smoking, dyslipidemia, hypertension, and HbA1c. Subsequently, we developed another four models: model 2, predictors in model 1 plus fasting plasma glucose (FPG); model 3, predictors in model 1 plus HOMA-IR and HOMA-β; model 4, predictors in model 1 plus FPG, HOMA-IR, and HOMA-β; model 5, replaced BMI with VFA in model 2. We assessed model discrimination and calibration for the first 10 years of follow-up.

RESULTS

The addition of FPG to model 1 obviously increased the value of the area under the receiver operating characteristic curve from 0.79 (95% CI 0.78, 0.81) to 0.84 (0.83, 0.85). Compared with model 1, model 2 also significantly improved the risk reclassification and discrimination, with a continuous net reclassification improvement index of 0.61 (0.56, 0.70) and an integrated discrimination improvement index of 0.09 (0.08, 0.10). Adding HOMA-IR and HOMA-β (models 3 and 4) or replacing BMI with VFA (model 5) did not further materially improve the performance.

CONCLUSIONS

This cohort study, primarily composed of male workers, suggests that a model with BMI, FPG, and HbA1c effectively identifies those at high diabetes risk. However, adding HOMA-IR, HOMA-β, or replacing BMI with VFA does not significantly improve the model. Further studies are needed to confirm our findings.