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.
Highlights
Glioblastoma multiforme (GBM) is the most common and lethal type of cerebral tumor, accounting for 15.1% of all central nervous system tumors, with an incidence rate of 3.19 per 100,000 individuals [1, 2]
Accumulating studies have demonstrated that peripheral blood test parameters play a remarkable role in the prognosis of various malignant tumors, such as lung cancer, gastric cancer, colorectal cancer, and hepatocellular carcinoma, as well as GBM [12,13,14,15, 31,32,33]
A recent scoring system developed by He et al based on the combination of plasma FIB and albumin levels can predict progression-free survival and overall survival (OS) in patients with highgrade gliomas [34]
Summary
Glioblastoma multiforme (GBM) is the most common and lethal type of cerebral tumor, accounting for 15.1% of all central nervous system tumors, with an incidence rate of 3.19 per 100,000 individuals [1, 2]. Several studies have indicated that a state of preoperative hypercoagulability is related to poor prognosis in patients with GBM [16, 17] Other factors such as glucose (GLC) [18, 19], hemoglobin (HBG) [20, 21], the prognostic nutrition index (PNI) [14, 22, 23], lactate dehydrogenase (LDH) [24, 25] and red blood cell distribution width (RDW) [20, 26] have been shown to have prognostic value in GBM. We aimed to establish a comprehensive prognostic scoring system containing hematological markers to improve the prognostic prediction in patients with glioblastoma
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