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1.
Medicine (Baltimore) ; 99(10): e19416, 2020 Mar.
Article in English | MEDLINE | ID: mdl-32150092

ABSTRACT

The present study aimed to develop an effective nomogram for predicting the overall survival (OS) of patients with cerebral anaplastic glioma (AG).This study included 1939 patients diagnosed with AG between 1973 and 2013 who were identified using the Surveillance, Epidemiology, and End Results database. A multivariate Cox regression analysis revealed that age, histology, tumor site, marital status, radiotherapy, and surgery were independent prognostic factors and, thus, these factors were selected to build a clinical nomogram. Harrell's concordance index (C-index) and a calibration curve were formulated to evaluate the discrimination and calibration of the nomogram using bootstrapping.A nomogram was developed to predict 5- and 9-year OS rates based on 6 independent prognostic factors identified in the training set: age, tumor site, marital status, histology, radiotherapy, and surgery (P < .05). The Harrell's concordance index values of the training and validation sets were 0.776 (0.759-0.793) and 0.766 (0.739-0.792), respectively. The calibration curve exhibited good consistency with the actual observation curve in both sets.Although the prognostic value of the World Health Organization (WHO) classification has been validated, we developed a novel nomogram based on readily available clinical variables in terms of demographic data, therapeutic modalities, and tumor characteristics to predict the survival of AG patients. When used in combination with the WHO classification system, this clinical nomogram can aid clinicians in making individualized predictions of AG patient survival and improving treatment strategies.


Subject(s)
Brain Neoplasms/mortality , Cerebellum , Glioma/mortality , Nomograms , Adolescent , Adult , Aged , Aged, 80 and over , Brain Neoplasms/diagnostic imaging , Child , Child, Preschool , Female , Glioma/diagnostic imaging , Humans , Infant , Infant, Newborn , Male , Middle Aged , Prognosis , SEER Program , Survival Analysis , United States , Young Adult
2.
World Neurosurg ; 136: e469-e475, 2020 Apr.
Article in English | MEDLINE | ID: mdl-31953100

ABSTRACT

OBJECTIVE: The present study aimed to characterize the mechanism of fluid shear stress (FSS)-induced endothelial cell (EC) injury via protein kinase C alpha (PKCα)-mediated vascular endothelial cadherin (VE-cadherin) and p120-catenin (p120ctn) expression. METHODS: We designed a T chamber system that produced stable FSS on ECs in vitro. Human umbilical vein endothelial cells (HUVECs) in which PKCα was knocked down and normal HUVECs were cultured on the coverslips. FSS was impinged on these 2 types of ECs for 0 hours and 6 hours. The morphology and density of HUVECs were evaluated, and expression levels of phosphorylated PKCα, p120-catenin (p120ctn), VE-cadherin, phosphorylated p120ctn at S879 (p-S879p120ctn), and nuclear factor kappa B (NF-κB) were analyzed by Western blot. RESULTS: HUVECs exposed to FSS were characterized by a polygonal shape and decreased cell density. The phosphorylated PKCα level was increased under FSS at 6 hours (P < 0.05). In normal HUVECs during FSS, p120ctn and VE-cadherin were decreased, whereas p-S879p120ctn and NF-κB were increased, at 6 hours (P < 0.05). In HUVECs after PKCα knockdown, p120ctn and VE-cadherin were not significantly changed (P > 0.05), p-S879p120ctn was undetectable, but NF-κB was decreased (P < 0.05) at 6 hours. CONCLUSIONS: The possible mechanism of FSS-induced EC injury may be as follows: 1) PKCα induces low expression of p120ctn, which leads to activation of NF-κB and degradation of VE-cadherin; 2) PKCα-mediated phosphorylation of p120ctn at S879 disrupts p120ctn binding to VE-cadherin.


Subject(s)
Antigens, CD/metabolism , Cadherins/metabolism , Catenins/metabolism , Human Umbilical Vein Endothelial Cells/physiology , Protein Kinase C-alpha/metabolism , Stress, Physiological/physiology , Endothelium, Vascular/cytology , Endothelium, Vascular/physiology , Gene Knockdown Techniques , Humans , Delta Catenin
3.
World Neurosurg ; 130: e605-e612, 2019 Oct.
Article in English | MEDLINE | ID: mdl-31319188

ABSTRACT

OBJECTIVE: The present study aimed to develop and evaluate a nomogram for predicting the overall survival (OS) of patients with low-grade glioma (LGG). METHODS: Patients with LGG diagnosed from 1973 to 2013 were identified using the Surveillance, Epidemiology, and End Results (SEER) database. A total of 3732 patients were randomly divided into a training set (n = 2612) and a validation set (n = 1120). Univariate and multivariate Cox regression analyses of the clinical variables were performed to screen for significant prognostic factors. Next, a nomogram that included significant prognostic variables was formulated to predict for LGG. Harrell's concordance index (C-index) and calibration plots were formulated to evaluate the reliability and accuracy of the nomogram using bootstrapping according to the internal (training set) and external (validation set) validity. RESULTS: A nomogram was developed to predict the 5- and 9-year OS rates using 7 variables in the training set: age, tumor site, sex, marital status, histological type, tumor size, and surgery (P < 0.05). The C-index for internal validation, which the nomogram used to predict OS according to the training set, was 0.777 (range, 0.763-0.791), and the C-index for external validation (validation set) was 0.776 (range, 0.754-0.797). The results of the calibration plots showed that the actual observation and prediction values obtained by the nomogram had good consistency between the 2 sets. CONCLUSIONS: We have developed a ready-to-use nomogram model that includes clinical characteristics to predict OS. The nomogram might provide consultation and risk assessments for subsequent treatment of patients with LGG.


Subject(s)
Brain Neoplasms/mortality , Glioma/mortality , Adult , Age Factors , Brain Neoplasms/pathology , Female , Glioma/pathology , Humans , Male , Neoplasm Grading , Nomograms , Prognosis , Risk Assessment , Risk Factors , SEER Program , Sex Factors , Survival Rate
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