Endocrine Abstracts

JOINT1419

Background: Polycystic ovary syndrome (PCOS) is one of the common disorders affecting women of reproductive age. Insulin resistance (IR) plays a pivotal role in its pathogenesis, leading to metabolic complications such as hyperglycemia, dyslipidemia, and increased cardiovascular risk. The triglyceride-glucose (TyG) index, a surrogate marker of IR, has gained attention for its simplicity and diagnostic accuracy across metabolic disorders. This study aims to comprehensively assess the role of the TyG index in PCOS and its utility as a diagnostic and prognostic biomarker.

Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines. PubMed, Scopus, Embase, and Web of Science were searched up to December 2024. Observational studies reporting TyG indices in PCOS and control groups were included. Subgroup and meta-regression analyses explored sources of heterogeneity. Sensitivity analysis and publication bias assessments ensured robustness.

Results: Fifteen studies (7,175 participants) were analyzed. The TyG index was significantly higher in women with PCOS compared to controls (SMD 0.34, 95% CI 0.14–0.54, I² = 70.9%). Subgroup analysis revealed a significant association in Chinese studies (SMD 0.42, 95% CI 0.35–0.49, I² = 0%) and cross-sectional studies (SMD 0.45, 95% CI 0.32–0.57, I² = 3.2%). The TyG index exhibited excellent diagnostic accuracy for distinguishing PCOS from controls (AUC 0.86, 95% CI 0.80–0.94, I² = 80.8%). Similarly, the TyG-BMI index showed a significant association with PCOS (SMD 0.34, 95% CI 0.10–0.57, I² = 0%) and excellent diagnostic performance (AUC 0.81, 95% CI 0.75–0.88, I² = 0%). Meta-regression analysis identified no significant impact of age, BMI, or lipid profiles on heterogeneity.

Conclusion: This meta-analysis uniquely highlights the triglyceride-glucose index as a robust and clinically significant marker for PCOS women. While the homeostatic model assessment of insulin resistance (HOMA-IR) is widely used, its reliance on insulin measurements limits its practicality in routine clinical settings. In contrast, the TyG index, derived from simple triglyceride and fasting glucose measurements, provides a more accessible and cost-effective alternative, facilitating early screening for insulin resistance, particularly for identifying metabolic risks in the PCOS population. Given that PCOS encompasses a heterogeneous spectrum of metabolic, hormonal, and ovarian dysfunctions rather than a single uniform disease, future research should focus on stratifying the TyG index’s association with insulin resistance across different PCOS phenotypes. Establishing phenotype-specific thresholds and refining its predictive capabilities for long-term cardiometabolic outcomes will be crucial in optimizing risk assessment and personalized management in this heterogeneous population.