Diagnostic value of preoperative inflammatory markers in glioma patients

In recent years, the role of inflammatory reactions in cancer progression and prognosis has been emphasizedThe characteristics of the inflammatory response refer to changes in indicators such as white blood cells (WBC), neutrophils, lymphocytes, monocytes, platelets, and C-reactive levelsCurrent studies have confirmed that neutrophils/lymphocyte ratios (NLR), derived NLR (dNLR), platelet/lymphocyte ratios (PLRs), lymphocytes/monocytocell ratios (PLMs), and prognostic ationomic index (PNIIs) can assess treatment effectiveness and predict survival rates in a wide range of cancer patients; Shi-hao Zheng of Neurosurgery, Fujian Provincial Hospital, and others analyzed the value of inflammatory indicators for glioma diagnosis and treatment, and the results were published in the September 2018 issue of J Neurosurgresearchers collected data from patients diagnosed with glioma, hearing neuroma, meningioma, or non-lesions epilepsy in three hospitals from January 2011 to February 2016 and conducted retrospective analysisBy using non-parametric tests, the correlation between the above indicators and tumor classification was analyzed by comparing nLR, dNLR, PLR, LMR, and PNI values in patients with glioma, hearing neuroma, meningioma, non-lesions epilepsy and healthy controlThe diagnostic significance of these indicators and their pairing combinations for gliomas, especially GBM, was evaluated using ROC curvesThe results showed that 750 glioma patients, including Class I 81, Grade II 208, Class III 169 and IV (GBM) 292 cases; Preoperative NLR and dNLR values were higher in glioma patients than in healthy control groups, hearing neuromas, meningiomas, or non-lesions with epilepsy, while LMR and PNI were lowerPlR in glioma patients was higher than in healthy control groups and non-lesions with epilepsysubgroup analysis showed positive correlation between NLR, dNLR, PLR and tumor classification, but negative correlation between LMR, PNI and glioma tumor classificationFor glioma patients, the under-curve area (AUC) obtained from the ROC curve is 0.722 (0.697-0.747), dNLR is 0.696 (0.670-0.722), and PLR is 0.576 (0.549-0.604), LMR 0.760 (0.738-0.783) and PNI 0.672 (0.646-0.698)Better diagnostic effects can be achieved using the combination of NLR-LMR and dNLR-LMR, with AUC at 0.777 and 0.778, respectivelyIn addition, NLR (AUC 0.860; 95% CI, 0.832-0.887), dNLR (AUC 0.840; 95% CI, 0.810-0.869), PLR (AUC 0.678;95% CI, 0.641-0.0.LMR (AUC 0.837; 95% CI, 0.811-0.863) and PNI (AUC 0.740; 95% CI, 0.706-0.773) are significant for the diagnosis and predictive prognosis of GBM compared to other tumor groupsCompared to Patients with Grade I-III glioma, the AUC of GBM patients with NLR is 0.811 (95% CI, 0.778-0.844), dNLR is 0.797 (95% CI, 0.763-0.832), and PLR is 0 .662 (95% CI, 0.622-0.702), LMR at 0.743 (95% CI, 0.707-0.779) and PNI 0.661 (95% CI, 0.622-0.701)For pairing combinations, the NLR-LMR is the most accurate, the researchers found that the NLR-LMR combination as a non-invasive biomarker has a high sensitivity and specificity to the diagnosis of glioma, can be used for glioma and hearing neuroma and meningioma differential diagnosis, in GBM and low-level glioma differential diagnosis also has a higher value.