Chao Yang

Background: Glioblastoma (GBM) is the most common primary malignant brain tumour in adults. Patients with GBM are particularly susceptible to moderate‐to‐high frail. Frailty status has been associated with the outcome of many types of cancer, including GBM, although there is still little consensus regarding the specific criteria for assessing frailty status. This study aimed to determine the predictive significance of the modified frailty score (mFS) in GBM patients using haematological and sarcopenia indicators. Methods: Between January 2016 and September 2022, we enrolled 309 adult GBM patients. Data on demographics, haematological examination, and temporal muscle thickness (TMT) were collected and assessed. The prognostic relevance of the frailty parameters was established using Kaplan–Meier and Cox proportional model. The scoring systems were created by integrating these indicators. Variables with independent prognostic values were used to construct the nomograms. Nomogram accuracy was evaluated using the calibration curve, Harrell's concordance index (C‐index), and time‐dependent receiver operating characteristic curves. Clinical practicality was assessed using decision curve analysis. Results: The baseline characteristics of the 309 participants revealed a median age of 59 years (interquartile range 52–66) with a predominance of male patients (58.58%). TMT (hazard ratio [HR] = 3.787, 95% confidence interval [CI] 2.576–5.566, p < 0.001), prognostic nutritional index (HR = 1.722, 95% CI 1.098–2.703, p = 0.018), and mean corpuscular volume (HR = 1.958, 95% CI 1.111–3.451, p = 0.020) were identified as independent prognostic markers. The constructed mFS, obtained by integrating these three indices, exhibited independent prognostic significance (HR = 2.461, 95% CI 1.751–3.457, p < 0.001). The patients in the low‐risk group had a median overall survival (OS) of 13.9 months, while the patients in the high risk had a median OS of 5.8 months. Importantly, the mFS demonstrated significant independent prognostic value in the subgroup aged > 65 (HR = 1.822, 95% CI 1.011–3.284, p = 0.046). The nomogram, which included the mFS, demonstrated high accuracy, with a c‐index of 0.781. The nomogram bootstrapped calibration plot also performed well compared to the ideal model. Nomograms showed promising discriminative potential, with time‐dependent areas under the curves of 0.945, 0.835, and 0.820 for 0.5‐, 1‐, and 2‐year overall survival prediction, respectively. Conclusions: Preoperative mFS is a comprehensive frailty marker for predicting survival outcomes in patients with GBM. A dynamic nomogram incorporating the mFS may facilitate preoperative survival evaluation. Early and appropriate multimodal interventions, including nutritional support, rehabilitation, and psychological care, may help in the neurosurgical care of patients with GBM or other brain tumours.

Inflammation is strongly associated with cancers. Our research explored the prognostic role of hematological inflammatory indicators in patients with glioblastoma (GBM). Hundred patients were incorporated finally, and we determined the best cutoff values of these blood markers through X-tile first to perform further survival tests. The prognostic role of peripheral blood cell count and corresponding ratios were assessed using the Kaplan–Meier curve and Cox models to identify variables with independent prognostic significance. Then, variables with independent predictive values were incorporated in constructing the nomogram model to realize quantitative prediction for survival. Nomograms were evaluated using Harrell concordance index, receiver operating characteristic curves, and decision curve analysis to assess clinical benefit. Multivariate analysis indicated that a higher platelet-to-basophil ratio (PBR) (>4575) (hazard ratio = 1.819, 95% confidence interval: 1.110–2.980, P = .018) was associated with poorer overall survival in GBM patients. Based on the PBR nomogram, the predictive accuracy was moderate (concordance index = 0.844, area under curve = 0.632). The PBR could serve as a prognostic biomarker for overall survival in patients with GBM, and nomogram models incorporating the PBR could facilitate comprehensive preoperative survival assessment.

Tumor treating fields (TTFields) is a novel approved modality for the treatment of glioblastoma (GBM) exhibiting a satisfactory effect. Although TTFields has shown considerable safety for the normal brain, dermatological adverse events (DAEs) often occur during therapy. However, studies focused on the identification and management of DAEs are rare. The clinical data and photos of skin lesions from 9 patients with GBM were retrospectively analyzed, and the types and grades of individual scalp dermatitis were evaluated based on the Common Terminology Criteria for Adverse Events version 5.0 (CTCAE v 5.0). Adherence and safety were also evaluated on the basis of the device monitoring data. Eight patients (88.9%) exhibited grade 1 or grade 2 CTCAE DAEs, all of whom were cured after interventions. The adherence was >90%, with no relevant safety events reported. Finally, a guideline for preventing DAEs in patients with GBM was proposed. The identification and management of TTFields-related DAEs is necessary and urgent in patients with GBM. Timely interventions of DAEs will help to improve the adherence and quality of life of patients, which ultimately improves prognosis. The proposed guideline for preventing DAEs in patients with GBM assists in the management of healthcare providers and may avoid dermatologic complications.

The purpose was to evaluate the prognostic value of systemic immune-inflammation index (SII) in glioblastoma patients. A total of 100 patients were retrospectively analyzed. We performed Kaplan–Meier and Cox regression analyses to determine the prognostic significance of SII. A nomogram was constructed by incorporating independent prognostic variables. The predictive accuracies of nomograms were evaluated by Harrell concordance index (c-index) and receiver operating characteristic curve analysis; the clinical benefit was evaluated by decision curve analysis. A high SII (>510.8 × 10⁹ cells/L) (hazard ratio = 1.672, P = .034) and neutrophil count (>3.9 × 10⁹ cells/L) (hazard ratio = 1.923, P = .009) were independently related with poor outcome in glioblastoma patients based on Cox analysis. The nomogram incorporating SII showed a good predictive accuracy (c-index = 0.866). Preoperative SII and neutrophil count are potential prognostic biomarkers for overall survival in glioblastoma patients and the nomogram model that integrated the SII may be used to facilitate a comprehensive preoperative survival evaluation.

Inflammation is related to cancer. The systemic immune-inflammation index (SII) has been linked to the prognosis of many types of cancer. The present study aimed to determine the prognostic value of the SII in glioblastoma (GBM) patients based on meta-analysis and single-center retrospective analysis. Relevant publications published before 1 October 2022 were identified by searching PubMed, EMBASE, Cochrane Library databases, and Web of Science. Moreover, 208 GBM patients from Zhongnan Hospital were incorporated. Kaplan–Meier and Cox regression analyses determined the prognostic significance of inflammatory markers. By combining these indicators, we developed scoring systems. Nomograms were also built by incorporating independent variables. The accuracies of nomograms were evaluated by Harrell’s concordance index (c-index) and the calibration curve. According to meta-analysis, an elevated SII predicted the worst overall survival (OS) (Hazard ratio [HR] = 1.87, p < 0.001). Furthermore, a higher SII (>510.8) (HR = 1.782, p = 0.007) also predicted a poorer outcome in a retrospective cohort. The scoring systems of SII-NLR (neutrophil-to-lymphocyte ratio) showed the best predictive power for OS. The nomogram without MGMT (c-index = 0.843) exhibited a similar accuracy to that with MGMT (c-index = 0.848). A pre-treatment SII is independently associated with OS in GBM. A nomogram integrating the SII-NLR score may facilitate a comprehensive survival evaluation independent of molecular tests in GBM.

Glioma is one of the most commonly diagnosed intracranial malignant tumors with extremely high morbidity and mortality, whose treatment was seriously limited because of the unclear molecular mechanism. In this study, in order to identify a novel therapeutic target for glioma treatment, we explored the functions and mechanism of MEX3A in regulating glioma. The immunohistochemical staining of MEX3A in glioma and normal tissues revealed the upregulation of MEX3A and further indicated the relationship between high MEX3A expression and higher malignancy as well as poorer prognosis of glioma. In vitro loss-of-function and gain-of-function experiments comprehensively demonstrated that MEX3A may promote glioma development through regulating cell proliferation, cell apoptosis, cell cycle, and cell migration. In vivo experiments also suggested the inhibition of glioma growth by MEX3A knockdown. Moreover, our mechanistic study identifies CCL2 as a potential downstream target of MEX3A, which possesses similar regulatory effects on glioma development with MEX3A and could attenuate the promotion of glioma induced by MEX3A overexpression. Overall, MEX3A was identified as a potential tumor promoter in glioma development and therapeutic target in glioma treatment.