Levels of Systemic Inflammatory Markers in Women with Cervical Cancer Undergoing Definitive Chemoradiotherapy Depend Primarily on Pre-treatment and Post-teletherapy Tumor Volume, Rather than on the Prescribed Radiation Dose
Year: 2026
Type: article
Study design: Observational Study
Abstract: INTRODUCTION/OBJECTIVE: Cervical cancer (CC) remains a major global health problem, especially in advanced stages. Systemic inflammatory markers such as the neutrophil-tolymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII) have been proposed as prognostic indicators. This study evaluated treatment-related alterations in these markers and their associations with clinical factors. METHODS: In this prospective study, 106 women with FIGO stage IB-IVA CC treated with dCRT were analyzed. Peripheral blood was collected one day before treatment and within three days after teletherapy. Inflammatory indices were derived from complete blood counts, and tumor volumes were assessed by MRI. Associations with clinical and treatment parameters were explored using appropriate statistical methods. RESULTS: After teletherapy, NLR increased significantly (median 4.86 vs. 3.31, p = 0.022), PLR rose markedly (377.5 vs. 198.8, p < 0.001), and LMR decreased (1.35 vs. 2.49, p < 0.001). SII changes were not significant. Baseline indices correlated with pre-treatment tumor volume, while post-therapy NLR and LMR were associated with post-teletherapy tumor volume but not with radiation dose, histological grade, or FIGO stage. An exploratory Kaplan-Meier analysis suggested poorer outcomes with elevated NLR and PLR, although differences were not statistically significant. DISCUSSION: Observed alterations in NLR, PLR, and LMR suggest these markers reflect tumor burden and immune response dynamics during dCRT. CONCLUSION: NLR, PLR, and LMR undergo significant changes during dCRT, largely reflecting tumor burden rather than treatment parameters, supporting their role as dynamic biomarkers in CC.
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7119482138