A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma

Abstract

BackgroundGlioblastoma is the most common primary malignant brain tumor. Recent studies have shown that hematological biomarkers have become a powerful tool for predicting the prognosis of patients with cancer. However, most studies have only investigated the prognostic value of unilateral hematological markers. Therefore, we aimed to establish a comprehensive prognostic scoring system containing hematological markers to improve the prognostic prediction in patients with glioblastoma.Patients and MethodsA total of 326 patients with glioblastoma were randomly divided into a training set and external validation set to develop and validate a hematological-related prognostic scoring system (HRPSS). The least absolute shrinkage and selection operator Cox proportional hazards regression analysis was used to determine the optimal covariates that constructed the scoring system. Furthermore, a quantitative survival-predicting nomogram was constructed based on the hematological risk score (HRS) derived from the HRPSS. The results of the nomogram were validated using bootstrap resampling and the external validation set. Finally, we further explored the relationship between the HRS and clinical prognostic factors.ResultsThe optimal cutoff value for the HRS was 0.839. The patients were successfully classified into different prognostic groups based on their HRSs (P < 0.001). The areas under the curve (AUCs) of the HRS were 0.67, 0.73, and 0.78 at 0.5, 1, and 2 years, respectively. Additionally, the 0.5-, 1-y, and 2-y AUCs of the HRS were 0.51, 0.70, and 0.79, respectively, which validated the robust prognostic performance of the HRS in the external validation set. Based on both univariate and multivariate analyses, the HRS possessed a strong ability to predict overall survival in both the training set and validation set. The nomogram based on the HRS displayed good discrimination with a C-index of 0.81 and good calibration. In the validation cohort, a high C-index value of 0.82 could still be achieved. In all the data, the HRS showed specific correlations with age, first presenting symptoms, isocitrate dehydrogenase mutation status and tumor location, and successfully stratified them into different risk subgroups.ConclusionsThe HRPSS is a powerful tool for accurate prognostic prediction in patients with newly diagnosed glioblastoma.

Sequential Evaluation of Hematology Markers as a Prognostic Factor in Glioblastoma Patients

“…The second area of focus was the longitudinal variability of these indicators throughout the disease course, including throughout treatment. By assessing how the NLR, PLR, and RDW fluctuated over time, we sought to gain perceptions of the disease's progression and the effectiveness of treatment modalities [23]. This longitudinal analysis is essential, as it may uncover temporal patterns that might serve as early indicators of treatment success or failure and could potentially predict disease recurrence or progression.…”

A Clinical Prognostic Model Based on Preoperative Hematological and Clinical Parameters Predicts the Progression of Primary WHO Grade II Meningioma

“…The “net” constructed by FIB in the extracellular matrix promotes cell adhesion and tumor invasion ( 30 ); in addition, FIB ultimately promotes angiogenesis and tumor growth by binding to growth factors such as vascular endothelial growth factor and fibroblast growth factor-2 ( 31 , 32 ). Previous studies have found that a high level of DD induces the progression of oral squamous cell carcinoma, cervical cancer, and glioma ( 13 , 19 , 33 ). In our study, the AUCs of FIB and DD for the diagnosis of meningioma progression were 0.615 and 0.593 in the training cohort, respectively, and their weighting coefficients in the HRM were 0.199 and 0.712, respectively; this also confirmed that high levels of FIB and DD were risk factors for the progression of AM.…”

“…reported that preoperative neutrophil-to-lymphocyte ratio (NLR) and fibrinogen (FIB) were related to the PFS of patients with AM ( 11 ). Our previous study confirmed the prognostic value of lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and albumin-to-globulin ratio (AGR) in glioma ( 12 ); other factors, such as D-dimer (DD), hemoglobin (HBG), lactate dehydrogenase (LDH), and red blood cell distribution width (RDW), have also been shown to be correlated with clinical outcomes in patients with glioma ( 13 ). However, it remains unclear whether these parameters have any prognostic value in AM.…”