Evaluating the triglyceride glucose index as a predictive biomarker for osteoporosis in patients with type 2 diabetes - Zhan, Jinxiang; Wei, Qipeng; Guo, Weijun; Liu, Zihao; Chen, Shiji; Huang, Qingyan; Liang, Shuang; Cai, Dongling (Frontiers in Endocrinology, 2025)
ObjectiveOsteoporosis is a common condition among individuals with type 2 diabetes; however, the relationship between insulin resistance, as measured by the Triglyceride Glucose Index (TyG), and osteoporosis has not been sufficiently explored. This study seeks to address this research gap by investigating the diagnostic value of TyG in identifying osteoporosis in patients with type 2 diabetes.MethodsA retrospective analysis was performed on clinical data from 207 diabetic subjects (83 in the osteoporosis group, 124 in the non-osteoporosis group), using SPSS version 27.0 and MedCalc 23 for statistical analysis.ResultsSignificant statistical differences were noted between the two groups in terms of gender, age, hemoglobin levels, red blood cell count, total cholesterol levels, and the TyG. Binary logistic regression analysis revealed that gender, age, and TyG are independent predictors of osteoporosis in patients with type 2 diabetes. Receiver operating characteristic (ROC) analysis showed that the area under the curve for TyG, gender, age, and their combination in predicting osteoporosis among patients with T2DM was 0.653, 0.698, 0.760, and 0.857, respectively. Additionally, the diagnostic performance of the TyG value was effectively evaluated, determining 8.78 as the optimal cutoff value, with a corresponding sensitivity of 89.1% and specificity of 52.4%. Meanwhile, the predictive model constructed using gender, age, and the TyG index achieved an area under the curve (AUC) of 0.857 (95% confidence interval: 0.801~0.901), with a maximum Youden index of 0.629. The corresponding diagnostic sensitivity was 83.1% and the specificity was 79.8%.ConclusionThe TyG holds potential to serve as a prominent biomarker for the diagnosis of osteoporosis among type 2 diabetic patients in various clinical settings.