Related Experiment Video
Updated: May 15, 2025
Enhancing Tumor Content through Tumor Macrodissection
Published on: February 12, 2022
An analysis of the relationship of triglyceride glucose index with diffuse large B-cell lymphoma prognosis: a
QingQing Luo1, Zhixiang Lei1, Haizhou Miao2
1Department of Hematology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Objective:
Diffuse large B-cell lymphoma (DLBCL) as among the most common lymphomas is associated with insulin resistance (IR). The triglyceride-glucose (TyG) index, generally considered a surrogate marker for IR, has an uncertain prognostic value in DLBCL.
Methods:
We conducted a retrospective analysis of DLBCL patients who received R-CHOP therapy at the Second Affiliated Hospital of Nanchang University from January 2011 to December 2023. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors for overall survival (OS). Boruta algorithm was employed to strengthen the robustness of our analysis. Restricted cubic spline (RCS) analysis was used to explore the potential nonlinear relationship between the TyG index and OS. Subgroup analyses were conducted to assess the prognostic value of the TyG index across different patient subgroups. Finally, a nomogram model based on the TyG index was developed, and its predictive performance was evaluated using the area under the receiver operating characteristic curve (AUROC), calibration curves, and decision curve analysis (DCA).
Results:
A total of 186 DLBCL patients were included in this study. Univariate and multivariate Cox regression analyses identified the TyG index, Age, ECOG performance status, Ann Arbor stage, and lactate dehydrogenase levels as independent prognostic factors for DLBCL. The Boruta algorithm confirmed these variables as the most important prognostic factors. Kaplan-Meier analysis revealed significantly poorer OS in the high TyG index group. RCS analysis demonstrated a non-linear relationship between the TyG index and OS. Subgroup analyses further validated the TyG index as a significant prognostic factor across various patient subgroups. The TyG-based nomogram model outperformed the conventional International Prognostic Index (IPI), with AUROCs of 0.878, 0.809, and 0.867 for 1-year, 3-year, and 5-year OS, respectively. Calibration curves showed good agreement between the nomogram predictions and actual outcomes, and DCA highlighted the high clinical utility of the model.
Conclusion:
The TyG index is an independent prognostic factor in DLBCL patients, and the TyG-based nomogram model provides enhanced predictive accuracy compared to the IPI. Its simplicity and low cost make it a valuable tool for routine clinical prognostic assessment in DLBCL patients.
