Comparative Analysis of Interleukin-6 Levels in Polycystic Ovary Syndrome (PCOS) Patients With and Without Insulin...

Background Polycystic ovary syndrome (PCOS) is an endocrine disorder prevalent in reproductive-aged women, characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovaries. It is often associated with insulin resistance, increasing risks for metabolic disorders such as diabetes and cardiovascular disease. Elevated interleukin-6 (IL-6) levels indicate chronic inflammation, a key component in PCOS pathogenesis, though its precise role and diagnostic potential remain unclear. Objective This study aims to evaluate the relationship between IL-6 concentrations and the severity of insulin resistance in patients with PCOS and to assess the potential of IL-6 as a diagnostic biomarker for insulin resistance within these patients. Methodology This cross-sectional study was carried out from February 2024 to January 2025 at the Departments of Medicine and Gynecology, Mardan Medical Complex Teaching Hospital, Khyber Pakhtunkhwa, Pakistan. Patients were divided into insulin-resistant and non-insulin-resistant groups based on clinical assessments. Pearson correlation and linear regression analyses were employed to investigate the relationship between IL-6 levels and study variables, adjusting for significant correlations and potential confounders. The relationship between insulin resistance and IL-6 levels was examined through linear regression. The study also evaluated IL-6's predictive ability for insulin resistance using receiver operating characteristic (ROC) curve analysis, calculating the area under the curve (AUC), with a significance threshold set at p<0.05. Results This study includes 112 patients with PCOS, and significant differences were identified between insulin-resistant (39.29%, 44 patients) and non-insulin-resistant patients (60.71%, 68 patients). IL-6 levels were notably higher in insulin-resistant patients (287.00±84.33 pg/mL) compared to non-resistant patients (159.16±52.36 pg/mL). PCOS patients revealed a complex relationship better described by a simple linear regression model (R²=0.56). Additionally, ROC curve analysis demonstrated the classifier's high diagnostic accuracy (AUC=0.91) Conclusion IL-6 levels in PCOS patients were significantly influenced by a combination of physiological, metabolic, and symptomatic factors. BMI, polycystic ovaries, and specific metabolic markers emerged as key predictors, underscoring the multifaceted role of IL-6 in the pathophysiology of PCOS.