Prognostic value of preoperative hematological markers in patients with glioblastoma multiforme and construction of random survival forest model

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 de...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:BMC cancer 2023-05, Vol.23 (1), p.432-432, Article 432
Hauptverfasser: Duan, Xiaozong, Yang, Bo, Zhao, Chengbin, Tie, Boran, Cao, Lei, Gao, Yuyuan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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. 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. 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 
ISSN:1471-2407
1471-2407
DOI:10.1186/s12885-023-10889-0