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Tumor-treating fields (TTF) is a novel cancer treatment that uses alternating electric fields to interfere with tumor cell mitosis. It has been approved by the U.S. food and drug administration for the treatment of recurrent glioblastoma (rGBM). We designed this meta-analysis to evaluate the efficacy and safety of TTF in the treatment of rGBM.The study was based on the PRISMA guideline. Systematic retrieval was performed in PubMed, Cochrane Library, and Embase databases. The outcomes were overall survival (OS) hazard ratio (HR), 1-year survival rate, and cutaneous toxicity.These studies included a total of 1048 rGBM patients who received TTF treatment. The overall survival time between the TTF group and the control group was HR 0.75 ([95%CI 0.63 to 0.89]; P = 0.001). Pooled 1-year overall survival rate and incidence of cutaneous toxicity were 0.47 and 0.48, respectively. Data were insufficient to evaluate the effect of MGMT methylation status and tumor recurrence times on heterogeneity.TTF therapy is effective for recurrent glioblastoma. However, most relevant trials should assess rGBM patient baseline characteristics such as age, KPS, MGMT methylation status, and number of tumor recurrence,. In addition, the risk of rashes caused by long-term wearing of devices should also be considered.

Background The tumor microenvironment (TME) plays an important role in cancer progression. We investigated TME-specific gene signatures and established a risk score to predict the outcome of medulloblastoma (MB) patients. Methods We evaluated TME parameters of 240 MB patients at Beijing Tiantan Hospital Capital Medical University with the ESTIMATE algorithm. Co-expression network analysis of differentially expressed and weighted genes (WGCNA) was used to identify intersecting genes. Using least absolute shrinkage and selection operator regression and backward stepwise regression we obtained a TME-associated risk score (TMErisk) based on eight prognostic gene signatures (CEBPB, OLFML2B, GGTA1, GZMA, TCIM, OLFML3, NAT1, and CD1C), verified in a GEO dataset (GSE85217). Results The correlation between TMErisk and TME, immune checkpoint, mRNAsi, and tumor mutation burden (TMB) was analyzed. MB patients’ response to immunotherapy was evaluated using immune-phenoscore (IPS) and drug sensitivity. A high TMErisk score indicated a worse overall survival. TMErisk scores were negatively correlated with immune cells, immune checkpoints, and human leukocyte antigens. TMErisk scores correlated significantly negatively with TMB and IPS for specific molecular subtypes. Tumor mRNAsi was associated with TME-risk. Conclusions A prognostic model based on TME-specific gene signatures may be used as a biomarker for evaluating prognosis and predicting response to immunotherapy in MB patients.

Background The prognostic factors for survival in patients with ependymoma (EPN) remain controversial. The aim of this study was to establish a prognostic model for 5‐ and 10‐year survival probability nomograms for patients with EPN. Methods Clinical data from the Surveillance, Epidemiology, and End Results (SEER) database were used for patients diagnosed with ependymoma between 2000 and 2018 and were randomized 7:3 into a development set and a validation set. Factors significantly associated with prognosis were screened out using the least absolute shrinkage and selection operator (LASSO) regression. The calibration chart and consistency index (C‐index) are used to evaluate the discrimination and consistency of the prediction model. Decision curve analysis (DCA) was used to further evaluate the established model. Finally, prognostic factors selected by LASSO regression were evaluated using Kaplan–Meier (KM) survival curves. Results A total of 3820 patients were included in the prognostic model. Seven survival predictors were obtained by LASSO regression screening, including age, gender, morphology, location, size, laterality, and resection. The prognostic model of the nomogram showed moderate discriminative ability in the development group and the validation group, with a C‐index of 0.642 and 0.615, respectively. In the development set and validation set survival curves, the prognosis index of high risk was less effective than low risk (p, Prognostic factors in patients with ependymoma (EPN) remain controversial. Based on the SEER database, we constructed prognosis models for EPN 5‐year and 10‐year survival rates. It may provide a reference for clinicians to personalized treatment.

Background The age of glioma plays a unique role in prognosis. We hypothesized that age is not positively correlated with survival prognosis and explored its exact relationship. Methods Glioma was identified from the SEER database (between 2000 and 2018). A multivariate Cox proportional regression model and restricted cubic spline (RCS) plot were used to assess the relationship between age and prognosis. Results A total of 66465 patients with glioma were included. Hazard ratios (HR) for ten-year by age: 0–9 years, HR 1.06 (0.93–1.20); 10–19 years: reference; 20–29 years, HR 0.90 (0.82–1.00); 30–39 years, HR 1.14 (1.04–1.25); 40–49 years, HR 2.09 (1.91–2.28); 50–59 years, HR 3.48 (3.19–3.79); 60–69 years, HR 4.91 (4.51–5.35);70–79 years, HR 7.95 (7.29–8.66); 80–84 years, HR 12.85 (11.74–14.06). After adjusting for covariates, the prognosis was not positively correlated with age. The smooth curve of RCS revealed this non-linear relationship: HR increased to 10 years first, decreased to 23 years, reached its lowest point, and became J-shaped. Conclusion The relationship between age and glioma prognosis is non-linear. These results challenge the applicability of current age groupings for gliomas and advocate the consideration of individualized treatment guided by precise age.

In recent randomized controlled studies, the prevention of stroke and cognitive function of ticagrelor has been controversial. We conducted a meta-analysis to compare ticagrelor with other antiplatelet treatment in patients with vascular high-risk factors disease, defined as acute coronary syndrome, stroke or transient ischemic attack, coronary artery disease or peripheral artery disease.We searched the PubMed, Embase, and Cochrane libraries for published randomized controlled trials and additional available data from ClinicalTrials.gov. The primary outcome was related adverse stroke events and the secondary outcome was cognitive function related adverse events. The outcomes were statistically analyzed using Peto odds ratio.12 RCTs with 105,654 patients were included in meta-analysis.all stroke (OR 0.84, 95%CI 0.78-0.90, P 0.001); Secondary outcomes: ischemic stroke (OR 0.83, 95%CI 0.77-0.90, P 0.001), transient ischemic attack (OR 0.78, 95%CI 0.62-0.97, P = 0.029), intracranial hemorrhage (OR 1.33, 95%CI 1.09-1.61, P = 0.005), Parkinson's disease (OR 0.30, 95%CI 0.12-0.72, P = 0.007), dementia (OR 0.31, 95%CI 0.13-0.77, P = 0.012), dizziness (OR: 1.39, 95%CI 1.03-1.87, P = 0.032), insomnia (OR 1.45, 95%CI 1.05-2.00, P = 0.026).Ticagrelor may provide more favorable outcomes for all stroke, ischemic stroke, and transient ischemic attack prevention in patients with vascular high-risk factors. However, this benefit may come with the cost of intracranial hemorrhage, dizziness and insomnia. Ticagrelor may reduce the risk of dementia and Parkinson's disease, although available data are limited.

Background: The prognostic risk factors for primary central nervous system (CNS) germ cell tumors (GCTs) in children and adolescents remain controversial. This study aimed to develop and validate a nomogram that predicts 5-and 10-year survival rates for CNS GCTs in children and adolescents.Methods: Pediatric with intracranial GCTs in the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2018 were analyzed. All GCTs children were randomly divided into the development group (70%) and the validation group (30%). The least absolute shrinkage and selection operator (LASSO) was used to screen the characteristic variables, and the 5- and 10-year survival probability nomogram was constructed. The accuracy of the nomogram was evaluated by consistency index (C-index), calibration plot, receiver operating characteristic curve (ROC), decision curve analysis (DCA) and survival curve.Results: We identified 819 cases of CNS GCTs in children. Three variables (histology, site and size) were selected by lasso regression to construct the nomogram. The C-index of the development group and verification group is 0.744 and 0.759. According to the time points of 5 and 10 years, the area under the curve of the development group is 0.753 and 0.696, and the verification set is 0.787 and 0.718. The results show that the prognostic nomogram developed by us has good accuracy.Conclusions: This is the first prognostic nomogram of CNS GCTs in children and adolescents. It can effectively predict the 5- and 10-year survival probability of children. It provides a useful prediction tool for clinicians.