DIAGNOSTIC UTILITY OF PRE TREATMENT NLR,PLR & MPV/ PC IN CERVICAL CANCER STAGING
Main Article Content
Keywords
Cervical cancer, Neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Mean platelet volume (MPV), Platelet count, Hematologic biomarkerCervical cancer, Neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Mean platelet volume (MPV), Platelet count, Hematologic biomarkers, Cancer Staging, Inflammatory markers.
Abstract
Background:Cervical cancer remains a significant public health issue, especially in developing countries. Early-stage identification is essential for initiating timely treatment and improving patient outcomes. Recent evidence suggests that systemic inflammatory markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume to platelet count ratio (MPV/PC) may aid in predicting cancer progression.
Objective:To evaluate the diagnostic utility of pretreatment NLR, PLR, and MPV/PC ratios in differentiating early (Stage I–II) and late (Stage III–IV) cervical cancer patients.
Methods:A prospective study was conducted on 100 newly diagnosed, treatment-naïve cervical cancer patients. NLR, PLR, and MPV/PC ratios were calculated using pretreatment complete blood counts. Receiver operating characteristic (ROC) curve analysis was employed to determine cut-off values. Statistical significance was assessed using t-tests and chi-square tests, with p-values <0.05 considered significant.
Results:NLR (cutoff 4): Sensitivity 64.5%, Specificity 78.3%, p ˂0.0001
PLR (cutoff 150): Sensitivity 74.2%, Specificity 71%, p˂0.0001
MPV/PC (cutoff 4.8): Sensitivity 58.1%, Specificity 56.5%, p 0.134
PLR demonstrated the highest diagnostic sensitivity and strongest statistical association with late-stage disease, followed by NLR. MPV/PC showed a lower sensitivity and lacked statistical significance.
Conclusion:Pretreatment inflammatory markers, particularly PLR and NLR, are significantly associated with the stage of cervical cancer and can serve as cost-effective, non-invasive tools for clinical risk stratification. Incorporating these parameters into routine pre-treatment evaluation may assist in early-stage identification and individualized treatment planning.
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Pushpkunjika Sharma
Junior resident, Shyam shah medical college Rewa,
Priyanka Agrawal
Dr Priyanka Agrawal , Professor, Shyam shah medical college , Rewa
Lokesh Tripathi
Dr Lokesh Tripathi, Associate professor, Shyam shah medical college , Rewa ,
SK Sutrakar
Dr S K Sutrakar, Professor and Head of the department, Shyam shah medical college , Rewa ,
Deepti Tiwari
Dr Deepti Tiwari, Junior resident, shyam shah medical college Rewa ,
Vibha Misra
Dr Vibha Misra, Junior resident, Shyam shah medical college Rewa,
Shambhavi
Dr Shambhavi, Shyam shah medical college Rewa ,
Parul Singh Rajpoot
Dr Parul Singh Rajpoot, Shyam shah medical college Rewa,
