ArticleFrontiers in endocrinology2025
The atherogenic index of plasma and triglyceride-glucose index as promising predictors of overall and disease-free survival in postoperative breast cancer patients.
Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Insulin resistance (IR) is closely linked to breast cancer development and prognosis. This study aimed to evaluate the prognostic value of four surrogate indices of IR, the atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, TyG index combined with body mass index (TyG-BMI), and metabolic score for IR (METS-IR), for overall survival (OS) and disease-free survival (DFS) in postoperative breast cancer patients. Methods: This retrospective cohort study included 298 patients with primary breast cancer who underwent radical surgery. We used multivariable Cox regression, Kaplan-Meier analysis, restricted cubic splines, receiver operating characteristic (ROC) curves, and subgroup analyses to assess associations and predictive performance for 3-, 5-, and 10-year survival. Random survival forest analysis ranked the importance of IR-related variables. Results: In fully adjusted models, elevated AIP and TyG index were significantly associated with worse OS, with hazard ratios of 2.28 and 2.82, respectively, for the highest versus lowest tertiles. Per 1-standard-deviation (SD) increase in AIP and TyG was associated with a 50% and 55% increased risk of OS, respectively. For DFS, only the TyG index showed a statistically significant association in the tertile comparison. Notably, Kaplan-Meier analysis and multivariable Cox models consistently indicated significant associations for AIP and TyG with OS and DFS. The predictive performance of AIP and TyG as assessed by ROC analysis was similar to each other but superior to TyG-BMI and METS-IR across all time points. Random survival forest (RSF) analysis identified AIP and TyG as the most important variables for predicting OS and DFS, respectively. Subgroup analyses revealed consistent trends for AIP and TyG across different patient subgroups. Conclusion: Our findings suggest that the AIP and TyG index are promising, easily obtainable biomarkers for risk stratification and long-term survival prediction in breast cancer patients after radical surgery.
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