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In the United States, an individual’s access to resources, insurance status, and wealth are critical social determinants that affect both the risk and outcomes of many diseases. One disease for which the correlation with socioeconomic status (SES) is less well-characterized is glioblastoma (GBM), a devastating brain malignancy. The aim of this study was to review the current literature characterizing the relationship between area-level SES and both GBM incidence and prognosis in the United States. A query of multiple databases was performed to identify the existing data on SES and GBM incidence or prognosis. Papers were filtered by relevant terms and topics. A narrative review was then constructed to summarize the current body of knowledge on this topic. We obtained a total of three papers that analyze SES and GBM incidence, which all report a positive correlation between area-level SES and GBM incidence. In addition, we found 14 papers that focus on SES and GBM prognosis, either overall survival or GBM-specific survival. Those studies that analyze data from greater than 1,530 patients report a positive correlation between area-level SES and individual prognosis, while those with smaller study populations report no significant relationship. Our report underlines the strong association between SES and GBM incidence and highlights the need for large study populations to assess SES and GBM prognosis to ideally guide interventions that improve outcomes. Further studies are needed to determine underlying socioeconomic stresses on GBM risk and outcomes to identify opportunities for intervention. [ABSTRACT FROM AUTHOR]

Objective: Risk-standardized mortality rates (RSMRs) have recently been shown to outperform facility case volume as a proxy for surgical quality in lung and gastrointestinal cancer. The aim of this study was to investigate RSMR as a surgical quality metric in primary CNS cancer., Methods: This retrospective observational cohort study used data from the National Cancer Database, a population-based oncology outcomes database sourced from more than 1500 institutions in the United States, and included adult patients 18 years of age and older who were diagnosed with glioblastoma, pituitary adenoma, or meningioma and were treated with surgery. For each group, RSMR quintiles and annual volume were calculated in a training set (2009-2013) and these thresholds were applied to the validation set (2014-2018). In this paper, the authors compared the effectiveness and efficiency of facility volume-based versus RSMR-based hospital centralization models and evaluated the overlap between the two systems. A patterns-of-care analysis was also performed to explore socioeconomic predictors of being treated at better-performing treating facilities., Results: A total of 37,838 meningioma, 21,189 pituitary adenoma, and 30,788 glioblastoma patients were surgically treated from 2014 to 2018. There were substantial differences between RSMR and facility volume classification schemes among all tumor types. In an RSMR-based centralization model, an average of 36 patients undergoing glioblastoma surgery would need to relocate to a low-mortality hospital to prevent one 30-day mortality following surgery, whereas 46 would need to relocate to a high-volume hospital. For pituitary adenoma and meningioma, both metrics were inefficient in centralizing care to reduce surgical mortality. Additionally, overall survival for glioblastoma patients was better modeled in an RSMR classification scheme. Analyses to investigate the impact of care disparities found that Black and Hispanic patients, patients earning less than $38,000, and uninsured patients were more likely to be treated at high-mortality hospitals., Conclusions: RSMR is more effective and efficient than a traditional volume-based approach for preventing early postoperative death in glioblastoma surgery. These data have important implications for future quality-related studies in neurosurgical oncology and may be relevant for healthcare/insurance payments, hospital evaluation assessments, healthcare disparities, and the standardization of care across hospitals.

Background: Patients with glioblastoma multiforme (GBM) who undergo radiation often require anticonvulsants during treatment. The aim of this study was to determine the effects of anticonvulsants on GBM clinical outcomes., Methods: A retrospective analysis was performed using the SEER-Medicare database. All patients with GBM who were treated with radiation and concurrently taking an anticonvulsant were included in final analysis. Each class of medication was further subdivided by mechanism of action. Descriptive statistics were performed for all variables. Kaplan Meier survival curves were generated for each class of medication and Cox regression analysis was performed to assess the effect of each individual variable on survival., Results: There were 1561 patients available for final analysis. On multivariate Cox regression analysis, GBM patients taking sodium/calcium (Na/Ca) channel blocker anticonvulsants during radiation therapy demonstrated both improved overall survival (OS) (HR, 0.799; 95% CI [0.716, 0.891]; P < 0.001) and cancer specific survival (CSS) (HR, 0.814; 95% CI [0.727, 0.911]; P < 0.001)., Conclusion: OS was significantly better in patients taking NA/Ca channel blockers among patients with GBM who were concurrently undergoing radiation therapy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objectives: A bibliometric and knowledge-map analysis is used to explore hotspots' evolution and development trends in the CAR-T cell field. By looking for research hotspots and new topics, we can provide new clues and ideas for researchers in this field., Methods: The articles and reviews regarding CAR-T cells were retrieved and obtained from the Web of Science Core Collection (WOSCC) on October 28th, 2021. CtieSpace [version 5.8.R3 (64-bit)] and VOSviewer (version 1.6.17) were used to conduct the bibliometric and knowledge-map analysis., Results: 660 authors from 488 institutions in 104 countries/regions published 6,867 papers in 1,212 academic journals. The United States was absolutely in the leading position in this research field. The institution that contributed the most publications was the University of Pennsylvania. Carl H June published the most articles, while Shannon L Maude had the most co-citations. However, there was little cooperation between countries. After 2012, cooperation among various institutions was also small. The journals that published the most CAR-T cell-related papers were Frontiers in immunology and Cancers . Nevertheless, Blood and The New England Journal of Medicine were the most commonly co-cited journals. The most influential research hotspots were the research of CAR-T cells in hematological malignancies, the related research of cytokine release syndrome (CRS), CD19, and the anti-tumor activity and efficacy of CAR-T cells. The latest hotspots and topics included the study of CAR-T cells in solid tumors, universal CAR-T cells, CAR-NK cells, CD22, and anakinra (the IL-1 receptor antagonist). The research of CAR-T cells in solid tumors was a rapidly developing hot field. Emerging topics in this field mainly included the study of CAR-T cells in glioblastoma (related targets: IL13Rα2, EGFRvIII, and HER2), neuroblastoma (related target: GD2), sarcoma (related target: HER2), and pancreatic cancer (related target: mesothelin), especially glioblastoma., Conclusion: As an anti-tumor therapy with great potential and clinical application prospects, CAR-T cell therapy is still in a stage of rapid development. The related field of CAR-T cells will remain a research hotspot in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Miao, Zhang, Zhang, Wang, Tang, Teng and Li.)

Tumor-treating fields (TTFields) are a cancer treatment modality that uses alternating electric fields of intermediate frequency (∼100-500 kHz) and low intensity (1-3 V/cm) to disrupt cell division. TTFields are delivered by transducer arrays placed on the skin close to the tumor and act regionally and noninvasively to inhibit tumor growth. TTFields therapy is U.S. Food and Drug Administration approved for the treatment of glioblastoma multiforme, the most common and aggressive primary human brain cancer. Clinical trials testing the safety and efficacy of TTFields for other solid tumor types are underway. The objective of this paper is to review computational approaches used to characterize TTFields. The review covers studies of the macroscopic spatial distribution of TTFields generated in the human head, and of the microscopic field distribution in tumor cells. In addition, preclinical and clinical findings related to TTFields and principles of its operation are summarized. Particular emphasis is put on outlining the potential clinical value inferred from computational modeling.

This paper presents a method for the precise, accurate and efficient quantification of brain tumor (glioblastomas) via MRI that can be used routinely in the clinic. Tumor volume is considered useful in evaluating disease progression and response to therapy, and in assessing the need for changes in treatment plans. We use multiple MRI protocols including FLAIR, T1, and T1 with Gd enhancement to gather information about different aspects of the tumor and its vicinity. These include enhancing tissue, nonenhancing tumor, edema, and combinations of edema and tumor. We have adapted the fuzzy connectedness framework for tumor segmentation in this work and the method requires only limited user interaction in routine clinical use. The system has been tested for its precision, accuracy, and efficiency, utilizing 10 patient studies. The percent coefficient of variation (% CV) in volume due to operator subjectivity in specifying seeds for fuzzy connectedness segmentation is less than 1%. The mean operator and computer time required per study for estimating the volumes of both edema and enhancing tumor is about 16 min. The software package is designed to run under operator supervision. Delineation has been found to agree with the operators' visual inspection most of the time except in some cases when the tumor is close to the boundary of the brain. In the latter case, the scalp, surgical scar, or orbital contents are included in the delineation, and an operator has to exclude this manually. The methodology is rapid, robust, consistent, yielding highly reproducible measurements, and is likely to become part of the routine evaluation of brain tumor patients in our health system.

Background: Glioblastoma is an incurable disease with a poor prognosis. For caregivers of people with glioblastoma, the burden of care can be high. Patients often present with different clinical characteristics, which may impact caregiver burden in different ways. This study aimed to evaluate associations between patient clinical characteristics and caregiver burden/quality of life (QoL). Methods: Caregiver–patient dyads were enrolled at 7 academic cancer centers in the United States. Eligible caregiver participants were self-reported as the primary caregiver of an adult living with glioblastoma and completed a caregiver burden survey. Eligible patients were age ≥ 18 years at glioblastoma diagnosis and alive when their respective caregiver entered the study, with the presence of cognitive dysfunction confirmed by the caregiver. Data were analyzed with descriptive statistics and multivariable analyses. Results: The final cohort included 167 dyads. Poor patient performance status resulted in patient difficulty with mental tasks, more caregiving tasks, and increased caregiving time. Language problems were reported in patients with left-sided lesions. Patient confusion was negatively associated with all caregiver domains: emotional health, social health, general health, ability to work, confidence in finances, and overall QoL. Better caregiver QoL was observed in patients with frontal lobe lesions versus non-frontal lobe lesions. Conclusion: This study reinforced that patient performance status is a critical clinical factor that significantly affects caregiver burden, caregiving tasks, and caregiver time. Additionally, patient confusion affects multiple facets of caregiver burden/QoL. These results could be used to support guided intervention for caregiver support, customized to the patient experience. [ABSTRACT FROM AUTHOR]

Background: Gliomas are the most common type of primary malignant brain tumor in adults, representing one third of all primary and central nervous system (CNS) tumors and 80% of malignant tumors diagnosed in the Western world. Epidemiological data indicate that the overall incidence and mortality of cancer is higher in males, while females have a better prognosis. The goal of this study is to determine whether there are sex differences in the time to treat and clinical outcomes in patients with glioma Methods: Glioblastoma (GB) and Lower Grade Glioma (LGG) patients were defined per the Central Brain Tumor Registry of the United States (CBTRUS) from the National Cancer Database (NCDB) for diagnosis years 2004 to 2016. Associations between sex and time to treatment variables as well as associations between sex and multiple clinical outcomes were assessed using univariable and multivariable models. Results: A total of 176,100 patients were used for analysis (124,502 GBM and 51,598 LGG). Males had a statistically significant association with >7 days to surgery (OR = 1.09, CI 1.05–1.13, p < 0.001) but this association was not observed in the multivariable model (OR = 1.05, CI 0.96–1.16, p = 0.25). After adjustment for key variables including time to treat variables, males with GB and LGG had a higher risk of death (HR = 1.11, CI 1.09–1.13, p < 0.001, HR = 1.09, CI 1.03–1.15, p < 0.001; respectfully). Sex differences in 90-day mortality for GBM were not found after adjustment (OR for males = 0.99, CI 0.91–1.08, p = 0.93). For LGG, both the univariable and multivariable logistic regression models showed no sex differences in 90-day mortality (OR for males = 1.03, CI 0.94–1.12, p = 0.45; multivariable OR for males = 0.81, CI 0.62–1.06, p = 0.13). Conclusions: Based on NCDB data, there were no statistically significant differences in time to treatment between males and females, however males had a higher proportion of GB and LGG as well as a higher risk of death compared to females. [ABSTRACT FROM AUTHOR]