Longitudinal comparative performance of triglyceride-glucose-related indices and estimated glucose disposal rate for predicting metabolic syndrome risk
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Updated: Aug 5, 2026

Study of In Vivo Glucose Metabolism in High-fat Diet-fed Mice Using Oral Glucose Tolerance Test (OGTT) and Insulin Tolerance Test (ITT)
Published on: January 7, 2018
Salam Bennouar1,2, Abdelghani Bachir Cherif1, Mahrez Fissah1
1Faculty of Medicine, University Blida 1, Blida, Algeria.
Objective:
To compare the predictive performance of five insulin resistance (IR) indices for the risk of metabolic syndrome (MS) incidence.
Methods:
This is a cohort study including 1129 Algerian adults free of MS at baseline, followed for up to 49 months (median follow-up: 45 months; IQR, 22-49 months). Incident MS was defined according to the NCEP-ATPIII criteria. Five IR indices: triglyceride-glucose index (TYG), TYG-body mass index (TYG-BMI), TYG-waist circumference (TYG-WC), and estimated glucose disposal rate (eGDR), using BMI or WC, were evaluated using Cox models, adjusted for cardio-metabolic confounding factors. Their performance was evaluated using time-dependent ROC curves, Harrell's C-index, Kaplan-Meier curves, and incremental predictive improvement (net reclassification improvement (NRI) and integrated discrimination improvement (IDI)). Sensitivity analyses were performed using stratification based on gender, age, and baseline metabolic phenotypes.
Results:
During follow-up, 291 participants developed MS (25.8%). TYG-WC demonstrated the highest predictive performance among the evaluated indices within the NCEP-ATPIII framework: aHR = 1.44 per standard deviation (95% CI [1.24-1.66]). Values above 775.9 were associated with a 2.65-fold increased risk at the 49-month horizon, with a C-index of 0.83, mAUC of model curves of 0.828, and quasi-perfect calibration (slope = 0.984). It also provided the best incremental improvement (NRI = 0.076, IDI = 0.041). Indices incorporating waist circumference consistently demonstrated modestly better predictive performance than their BMI-based counterparts and showed significant improvement in risk reclassification (NRI), whereas BMI-based indices did not. The associations remained robust across gender, age, and obesity status.
Conclusion:
Within the NCEP-ATPIII framework, TYG-WC demonstrated the highest predictive performance among the evaluated indices and may represent a simple and clinically useful tool for metabolic risk stratification and early identification of individuals at increased risk of MS.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s40200-026-02021-3.
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