RESUMO
PURPOSE: High-grade gliomas (HGG) are aggressive cancers, and their recurrence is inevitable, despite advances in treatment options. While repeated tumor resection has been shown to increase survival rate, its impact on quality of life is not clearly defined. To address this gap, we compared quality of life (QoL) changes in HGG patients who underwent first-time (FTR) versus repeat surgical resections (RSR) for management of recurrence. METHODS: Forty-four adults with HGG who underwent tumor resection were included in this study and classified into either the FTR group (n = 23) or the RSR group (n = 21). All patients completed comprehensive neuropsychological evaluations that included the Functional Assessment of Cancer Therapy-General (FACT-G) and Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) scales, pre-operatively and at two weeks post-operatively. RESULTS: There was no difference between the FTR and RSR groups in any of the QoL indices (all p > .05), except for improved emotional well-being and worsened social well-being, suggesting minimal detrimental effects of repeat surgeries on QoL in comparison to first time surgery. CONCLUSIONS: These results suggest that repeated resection is a viable strategy in certain cases for management of HGG recurrence, with similar impact on QoL as observed in patients undergoing first time surgery. These encouraging outcomes provide useful insight to guide treatment strategies and patient and clinician decision making to optimize surgical and functional outcomes.
Assuntos
Neoplasias Encefálicas , Glioma , Adulto , Humanos , Neoplasias Encefálicas/patologia , Qualidade de Vida , Glioma/patologia , ReoperaçãoRESUMO
In vitro models of the human blood-brain barrier (BBB) are increasingly used to develop therapeutics that can cross the BBB for treating diseases of the central nervous system. Here we report a meta-analysis of the make-up and properties of transwell and microfluidic models of the healthy BBB and of BBBs in glioblastoma, Alzheimer's disease, Parkinson's disease and inflammatory diseases. We found that the type of model, the culture method (static or dynamic), the cell types and cell ratios, and the biomaterials employed as extracellular matrix are all crucial to recapitulate the low permeability and high expression of tight-junction proteins of the BBB, and to obtain high trans-endothelial electrical resistance. Specifically, for models of the healthy BBB, the inclusion of endothelial cells and pericytes as well as physiological shear stresses (~10-20 dyne cm-2) are necessary, and when astrocytes are added, astrocytes or pericytes should outnumber endothelial cells. We expect this meta-analysis to facilitate the design of increasingly physiological models of the BBB.
RESUMO
BACKGROUND: Intramedullary spinal cord tumors are challenging to resect, and their postoperative neurological outcomes are often difficult to predict, with few studies assessing this outcome. METHODS: We reviewed the medical records of all patients surgically treated for Intramedullary spinal cord tumors at our multisite tertiary care institution (Mayo Clinic Arizona, Mayo Clinic Florida, Mayo Clinic Rochester) between June 2002 and May 2020. Variables that were significant in the univariate analyses were included in a multivariate logistic regression. "MissForest" operating on the Random Forest algorithm, was used for data imputation, and K-prototype was used for data clustering. Heatmaps were added to show correlations between postoperative neurological deficit and all other included variables. Shapley Additive exPlanations were implemented to understand each feature's importance. RESULTS: Our query resulted in 315 patients, with 160 meeting the inclusion criteria. There were 53 patients with astrocytoma, 66 with ependymoma, and 41 with hemangioblastoma. The mean age (standard deviation) was 42.3 (17.5), and 48.1% of patients were women (n = 77/160). Multivariate analysis revealed that pathologic grade >3 (OR = 1.55; CI = [0.67, 3.58], P = 0.046 predicted a new neurological deficit. Random Forest algorithm (supervised machine learning) found age, use of neuromonitoring, histology of the tumor, performing a midline myelotomy, and tumor location to be the most important predictors of new postoperative neurological deficits. CONCLUSIONS: Tumor grade/histology, age, use of neuromonitoring, and myelotomy type appeared to be most predictive of postoperative neurological deficits. These results can be used to better inform patients of perioperative risk.