Key result
TG/HDL-C ratio best predicts metabolic syndrome in T2DM with an AUC of ~0.92.
Why the study?
Do surrogate indices of insulin resistance predict the presence of metabolic syndrome in hospitalized patients with type 2 diabetes mellitus?
Observational (n=2,409)
No
Do surrogate indices of insulin resistance predict the presence of metabolic syndrome in hospitalized patients with type 2 diabetes mellitus?
Effect estimate: C-index 0.922 (95% CI 0.909-0.936)
The TG/HDL-C ratio is a strong predictor of metabolic syndrome in patients with type 2 diabetes, and a nomogram incorporating it can aid in early clinical identification.
Objectives To evaluate the predictive value of surrogate indices of insulin resistance (IR)- specifically, the triglyceride-glucose (TyG) index, the triglyceride glucose-body mass (TyG-BMI) index, and the triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) for metabolic syndrome (MetS) in patients with type 2 diabetes mellitus (T2DM). Methods A single-center, retrospective study was conducted involving 2409 T2DM patients. Based on the presence of MetS, participants were divided into a T2DM-MetS group (n=1,787) and a T2DM-only group (n=622). Logistic regression was used to analyze the influencing factors for T2DM complicated with MetS, and to compare the predictive value of the TyG index, the TyG-BMI index, and the TG/HDL-C ratio. A nomogram prediction model was constructed. The model’s discriminative ability, clinical utility, and calibration were evaluated using the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and a calibration curve, respectively. Results The multivariate logistic regression analysis model revealed that Sex, Wasit-to-hip ratio (WHR), fasting C-Peptide (FCP), 2-hour C-Peptide (2hCP), the TyG index, the TyG-BMI index, and the TG/HDL-C ratio were risk factors for T2DM complicated with MetS. The area under the curve (AUC) for the TyG index, the TyG-BMI index, and the TG/HDL-C ratio in predicting T2DM complicated with MetS were 0.809, 0.807, and 0.915, respectively. The prediction model was constructed using the TG/HDL-C ratio, Sex, WHR, and FCP. The model demonstrated that the C-index for predicting the presence of MetS in T2DM patients was 0.922 (95% CI: 0.909, 0.936). The DCA showed a maximum net benefit rate of 0.742. Conclusions The surrogate indices for IR (the TyG index, the TyG-BMI index, and the TG/HDL-C ratio) were risk factors for T2DM complicated with MetS, among which the TG/HDL-C ratio was the optimal predictor. The nomogram model constructed based on the TG/HDL-C ratio, Sex, WHR, and FCP demonstrated good predictive performance for T2DM complicated with MetS. This model shows good calibration and practicality, providing a valuable reference to aid in early identification and preventive strategies in clinical practice.
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Xin et al. (2026) conducted an observational in Type 2 diabetes mellitus complicated with metabolic syndrome (n=2,409). Surrogate indices of insulin resistance (TyG, TyG-BMI, TG/HDL-C) was evaluated on Presence of metabolic syndrome (MetS) (C-index 0.922, 95% CI 0.909-0.936). The TG/HDL-C ratio was the optimal surrogate index for predicting metabolic syndrome in T2DM patients (AUC 0.915), and a combined nomogram model yielded a C-index of 0.922 (95% CI 0.909-0.936).
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