Blood-based inflammatory biomarkers in ovarian cancer: addressing the challenge of early detection, metastasis, and prognostic stratification

Ovarian cancer remains a major cause of gynaecological cancer mortality, largely because early disease is frequently asymptomatic and reliable population-based screening remains unavailable. Systemic inflammation is increasingly recognised as an important component of ovarian cancer biology, linking tumour progression, immune dysregulation, angiogenesis, metastasis and treatment resistance. This narrative review critically evaluates blood-based inflammatory biomarkers, including C-reactive protein, interleukin-6, interleukin-8, tumour necrosis factor-α, fibrinogen, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index (SII), systemic inflammation response index (SIRI) and pan-immune-inflammation value (PIV), across early detection, metastatic assessment, treatment decision-making and prognostic stratification. Available evidence indicates that elevated inflammatory indices are consistently associated with advanced disease and adverse outcomes, although substantial heterogeneity exists in biomarker thresholds, populations, timing of measurement and analytical approaches. Recent evidence also suggests that preoperative NLR and SII may contribute to treatment selection, including neoadjuvant chemotherapy, although prognostic independence is not consistently demonstrated. Importantly, inflammatory biomarkers lack sufficient specificity for standalone ovarian cancer screening and should not replace CA-125, HE4, imaging or histopathological assessment. Their greatest clinical potential lies in multimarker models integrating systemic inflammatory, tumour-specific, molecular and clinical variables. Future research should prioritise prospective multicentre validation, standardised thresholds, longitudinal assessment and clinically interpretable prediction models to determine whether inflammatory profiling can advance precision risk stratification and treatment selection in ovarian cancer.