ABSTRACT
OBJECTIVE: In recent years, an increasing number of studies have revealed that patients' preoperative inflammatory response, coagulation function, and nutritional status are all linked to the occurrence, development, angiogenesis, and metastasis of various malignant tumors. The goal of this study is to determine the relationship between preoperative peripheral blood neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), platelet to lymphocyte ratio (PLR), and platelet to fibrinogen ratio (FPR). Prognostic nutritional index (PNI) and the prognosis of glioblastoma multiforme (GBM) patients, as well as establish a forest prediction model that includes preoperative hematological markers to predict the individual GBM patient's 3-year survival status after treatment. METHODS: The clinical and hematological data of 281 GBM patients were analyzed retrospectively; overall survival (OS) was the primary endpoint. X-Tile software was used to determine the best cut-off values for NLR, SII, and PLR, and the survival analysis was carried out by the Kaplan-Meier method as well as univariate and multivariate COX regression. Afterward, we created a random forest model that predicts the individual GBM patient's 3-year survival status after treatment, and the area under the curve (AUC) is used to validate the model's effectiveness. RESULTS: The best cut-off values for NLR, SII, and PLR in GBM patients' preoperative peripheral blood were 2.12, 537.50, and 93.5 respectively. The Kaplan-Meier method revealed that preoperative GBM patients with high SII, high NLR, and high PLR had shorter overall survival, and the difference was statistically significant. In addition to clinical and pathological factors. Univariate Cox showed NLR (HR = 1.456, 95% CI: 1.286 ~ 1.649, P < 0.001) MLR (HR = 1.272, 95% CI: 1.120 ~ 1.649, P < 0.001), FPR (HR = 1.183,95% CI: 1.049 ~ 1.333, P < 0.001), SII (HR = 0.218,95% CI: 1.645 ~ 2.127, P < 0.001) is related to the prognosis and overall survival of GBM. Multivariate Cox proportional hazard regression showed that SII (HR = 1.641, 95% CI: 1.430 ~ 1.884, P < 0.001) is also related to the overall survival of patients with GBM. In the random forest prognostic model with preoperative hematologic markers, the AUC in the test set and the validation set was 0.907 and 0.900, respectively. CONCLUSION: High levels of NLR, MLR, PLR, FPR, and SII before surgery are prognostic risk factors for GBM patients. A high preoperative SII level is an independent risk factor for GBM prognosis. The random forest model that includes preoperative hematological markers has the potential to predict the individual GBM patient's 3-year survival status after treatment,and assist the clinicians for making a good clinical decision.
