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TyG-GGT index predicts incident diabetes mellitus in a 5-year retrospective cohort of 8,678 screened participantsNew Blood Score Predicts Diabetes Risk Better Than Standard Tests
Frontiers in MedicinePublished April 21, 2026DOI ↗Editorial oversight: Dr. Amelia Tan, PhD · Internal Medicine & Chronic Disease
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Key Takeaway
Note that the TyG-GGT index predicts incident diabetes mellitus with an AUC of 0.732 in this retrospective cohort.
This retrospective cohort study included 8,678 participants who underwent comprehensive health screenings at Kuichong People's Hospital in Shenzhen. The primary exposure was the TyG-GGT index, and the primary outcome was incident diabetes mellitus observed over a 5-year follow-up period. Multivariable adjustments and subgroup analyses were performed to verify the stability of the findings.
Higher TyG-GGT levels were associated with an elevated risk of incident diabetes mellitus. The hazard ratio was 1.116 per 50-unit increase in TyG-GGT (95% CI: 1.041-1.196). A non-linear association was observed with a threshold value at 380; below this inflection point, the hazard ratio was 1.723 per 50-unit increase (95% CI: 1.500-1.979), while the association was not statistically significant above this value.
Regarding predictive capacity, the TyG-GGT index demonstrated the highest AUC value of 0.732. This exceeded the AUC values of triglycerides (0.635), GGT (0.649), fasting plasma glucose (0.660), and the TyG index (0.675). Time-dependent ROC analysis indicated that AUC values for TyG-GGT remained stable between 0.7292 and 0.7338 over a prediction horizon of 1.0 to 5.0 years.
Adverse events, serious adverse events, discontinuations, and tolerability were not reported. As an observational study, these results indicate association rather than causation. The TyG-GGT index may serve as a clinically useful predictor for early identification of high-risk individuals and optimizing clinical prevention and management of diabetes mellitus.
Why Doctors Need Better Tools
Standard blood tests look at sugar levels alone. But sugar is just one piece of the puzzle. Doctors want a clearer picture of how your body handles energy.
The Surprising Shift in Testing
We used to rely on single markers like fasting glucose. But here’s the twist. Combining two markers creates a stronger signal. This new score mixes fat and sugar data.
Think of your body like a car engine. Insulin resistance is like a clogged fuel line. The new score checks both the fuel and the engine heat. It gives a fuller view of the problem.
Researchers looked at over 8,000 adults in China. They tracked their health for five years. They wanted to see who developed diabetes.
The new score predicted diabetes better than old methods. It beat tests for triglycerides, liver enzymes, and sugar alone. The data stayed stable over the whole five-year period.
The Specific Number That Matters
There is a specific number that matters here. The study found a threshold value at 380. Below this point, the risk signal was very strong. Above it, the pattern changed slightly.
This does not mean this test is available for home use.
What Experts Say About It
Experts see this as a promising step forward. It offers a new way to spot risk before symptoms appear. It helps doctors prioritize who needs more attention.
You cannot order this test at a pharmacy yet. It is still part of a larger research effort. If you are worried about diabetes, talk to your doctor.
Why We Need More Data
This study was done in one city. Results might differ in other places. We need to confirm these findings with diverse groups.
Looking Toward Future Research
More trials are needed before this becomes standard care. Scientists will work to validate the score globally. Until then, focus on healthy habits and regular checkups.
ObjectiveResearch on the association between TyG-GGT index and diabetes mellitus (DM) risk remains scarce. This study aimed to investigate the relationship between TyG-GGT and DM incidence.MethodsThis retrospective cohort investigation enrolled 8,678 participants who underwent comprehensive health screenings at Kuichong People’s Hospital in Shenzhen from 2018 through 2023. Cox proportional hazards regression models were employed to assess the association between TyG-GGT and DM risk, and Cox proportional hazards regression model with restricted cubic spline functions was used to evaluate non-linear relationships. Subgroup analyses and sensitivity analyses further verified the stability of these findings. Finally, receiver operating characteristic (ROC) curve methodology and time-dependent ROC analysis were performed to determine the predictive capacity of TyG-GGT for incident DM within a 5-year period.ResultsFollowing multivariable adjustments, higher TyG-GGT levels were found to be associated with elevated DM risk, demonstrating an HR of 1.116 (95% CI: 1.041-1.196) per 50-unit increase in TyG-GGT. Additionally, a non-linear association between them was observed, exhibiting a threshold value at 380. When below this inflection point, the HR per 50-unit increase in TyG-GGT was 1.723 (95% CI: 1.500-1.979), while above this value the association was not statistically significant. Additionally, in predicting DM risk, TyG-GGT had the highest AUC value (0.732), while the AUC values of TG (0.635), GGT (0.649), FPG (0.660), and TyG (0.675) were all lower than this value. Time-dependent ROC analysis revealed that the AUC values of TyG-GGT remained stable between 0.7292-0.7338 over a prediction horizon of 1.0 to 5.0 years. The stability of these results was further corroborated via sensitivity analysis.ConclusionThis study found that TyG-GGT demonstrated an independent positive association and non-linear relationship with DM risk, with an inflection point at 380. TyG-GGT below 380 was associated with higher observed DM risk. Additionally, TyG-GGT exhibits discriminatory performance for DM risk assessment and may serve as a clinically useful predictor, thereby aiding clinicians in early identification of high-risk individuals and providing a novel perspective for optimizing clinical prevention and management of DM.
