PCOS phenotypes and hematological immune-inflammatory indices: A comparative evaluation

To evaluate hematological immune-inflammatory indices across different polycystic ovary syndrome (PCOS) phenotypes and assess their potential as diagnostic biomarkers. This retrospective cross-sectional study included 89 women aged 18-40 years diagnosed with PCOS according to the Rotterdam criteria, stratified into four phenotypes (A-D). Demographic, anthropometric, reproductive, biochemical, and hormonal data were extracted from clinical records. Hematological indices were calculated from complete blood counts. Group comparisons were performed using appropriate statistical tests, correlations with metabolic and hormonal parameters were assessed, and logistic regression analyses were conducted to identify independent predictors. Phenotype A demonstrated significantly higher body mass indeks (BMI), waist circumference, fasting glucose, insulin, and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) values compared with other phenotypes (all p < 0.01). Neutrophil-to-Lymphocyte Ratio (NLR), Monocyte-to-Lymphocyte Ratio (MLR), and Systemic Immune-Inflammation Index (SII) differed significantly across phenotypes, whereas Platelet-to-Lymphocyte Ratio (PLR) did not. ROC analysis revealed that SII had the highest discriminative ability (AUC=0.822, p < 0.001). NLR (AUC=0.663, p = 0.020) and MLR (AUC=0.642, p = 0.043) also showed moderate predictive value. Correlation analyses indicated positive associations of NLR and SII with total testosterone and Free Androgen Index (FAI), and negative correlations with Sex Hormone-Binding Globulin (SHBG) and High-Density Lipoprotein (HDL) cholesterol. Logistic regression identified BMI, SII, and LH/FSH ratio as independent predictors of specific phenotypes, further supporting their role as clinically relevant biomarkers. Hematological immune-inflammatory indices, particularly SII, may serve as cost-effective and accessible biomarkers for distinguishing PCOS phenotypes.