LAUSR

Background The predictive value of systemic inflammatory response index (SIRI) was confirmed in some malignant tumors. However, few studies investigated the prognostic value of SIRI in high-grade gliomas. This study aimed to evaluate the prognostic relationship of preoperative SIRI in high-grade gliomas and established a nomogram accordingly. Methods Data of operable high-grade glioma patients were analyzed. Kaplan-Meier, log-rank test, cox regression and propensity score matching (PSM) analysis were used to analyze survival. ROC curve and area under the curve (AUC) were used to compare the ability of preoperative SIRI, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and monocyte-lymphocyte ratio (MLR) to predict prognosis. A nomogram based on the results was established. The consistency index (C-index) was calculated and a calibration curve was drawn.The prediction effect of the nomogram and WHO grade was compared by AUC. Results A total of 105 patients were included. Kaplan-Meier survival analysis showed that the overall survival (OS) of grade III gliomas patients with lower preoperative SIRI (SIRI<1.26) was significantly prolonged (p=0.037), and grade IV gliomas patients with lower preoperative SIRI had a tendency to obtain longer OS (p = 0.107). Cox regression showed preoperative SIRI was an independent prognostic factor for grade IV and grade III glioma, however, in IDH mutant-type IV gliomas, patients with lower SIRI only showed a tendency to obtain better OS. Similar results were obtained in PSM. The prognostic value of SIRI were better than PLR and MLR by ROC analysis. And in grade IV gliomas, the predictive value of SIRI was better than NLR. The nomogram established based on preoperative SIRI, age, extent of resection, number of gliomas, MGMT methylation status and histological types (only in grade III gliomas) could predict the prognosis more accurately. Conclusion SIRI was valuable for prognosis prediction in high-grade glioma. The nomogram covering SIRI could more accurately predict the survival rate in operable high-grade glioma patients.