Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Added Value of Cognition in the Prediction of Survival in Low and High Grade Glioma.

ABSTRACT: Background: Diffuse gliomas, which are at WHO grade II-IV, are progressive primary brain tumors with great variability in prognosis. Our aim was to investigate whether pre-operative cognitive functioning is of added value in survival prediction in these patients. Methods: In a retrospective cohort study of patients undergoing awake craniotomy between 2010 and 2019 we performed pre-operative neuropsychological assessments in five cognitive domains. Their added prognostic value on top of known prognostic factors was assessed in two patient groups [low- (LGG) and high-grade gliomas (HGG]). We compared Cox proportional hazards regression models with and without the cognitive domain by means of loglikelihood ratios tests (LRT), discriminative performance measures (by AUC), and risk classification [by Integrated Discrimination Index (IDI)]. Results: We included 109 LGG and 145 HGG patients with a median survival time of 1,490 and 511 days, respectively. The domain memory had a significant added prognostic value in HGG as indicated by an LRT (p-value = 0.018). The cumulative AUC for HGG with memory included was.78 (SD = 0.017) and without cognition 0.77 (SD = 0.018), IDI was 0.043 (0.000-0.102). In LGG none of the cognitive domains added prognostic value. Conclusions: Our findings indicated that memory deficits, which were revealed with the neuropsychological examination, were of additional prognostic value in HGG to other well-known predictors of survival.

SUBMITTER: van Kessel E

PROVIDER: S-EPMC8639204 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Radiomics for pseudoprogression prediction in high grade gliomas: added value of MR contrast agent.

Project description:ObjectiveOur aim is to define the capabilities of radiomics in predicting pseudoprogression from pre-treatment MR images in patients diagnosed with high-grade gliomas using T1 non-contrast-enhanced and contrast-enhanced images.Material & methodsIn this retrospective IRB-approved study, image segmentation of high-grade gliomas was semi-automatically performed using 3D Slicer. Non-contrast-enhanced T1-weighted images and contrast-enhanced T1-weighted images were used prior to surgical therapy or radio-chemotherapy. Imaging data was split into a training sample and an independent test sample at random. We extracted 107 radiomic features by use of PyRadiomics. Feature selection and model construction were performed using Generalized Boosted Regression Models (GBM).ResultsOur cohort included 124 patients (female: n = 53), diagnosed with progressive (n = 61) and pseudoprogressive disease (n = 63) of primary high-grade gliomas. Based on non-contrast-enhanced T1-weighted images of the independent test sample, the mean area under the curve (AUC), mean sensitivity, mean specificity and mean accuracy of our model were 0.651 [0.576, 0.761], 0.616 [0.417, 0.833], 0.578 [0.417, 0.750] and 0.597 [0.500, 0.708] to predict the development of pseudoprogression. In comparison, the independent test data of contrast-enhanced T1-weighted images yielded significantly higher values of AUC = 0.819 [0.760, 0.872], sensitivity = 0.817 [0.750, 0.833], specificity = 0.723 [0.583, 0.833] and accuracy = 0.770 [0.687, 0.833].ConclusionOur findings show that it is possible to predict pseudoprogression of high-grade gliomas with a Radiomics model using contrast-enhanced T1-weighted images with comparatively good discriminatory power. The use of a contrast agent results in a clear added value.

| S-EPMC9364026 | biostudies-literature

MEG network differences between low- and high-grade glioma related to epilepsy and cognition.

Project description:ObjectiveTo reveal possible differences in whole brain topology of epileptic glioma patients, being low-grade glioma (LGG) and high-grade glioma (HGG) patients. We studied functional networks in these patients and compared them to those in epilepsy patients with non-glial lesions (NGL) and healthy controls. Finally, we related network characteristics to seizure frequency and cognitive performance within patient groups.MethodsWe constructed functional networks from pre-surgical resting-state magnetoencephalography (MEG) recordings of 13 LGG patients, 12 HGG patients, 10 NGL patients, and 36 healthy controls. Normalized clustering coefficient and average shortest path length as well as modular structure and network synchronizability were computed for each group. Cognitive performance was assessed in a subset of 11 LGG and 10 HGG patients.ResultsLGG patients showed decreased network synchronizability and decreased global integration compared to healthy controls in the theta frequency range (4-8 Hz), similar to NGL patients. HGG patients' networks did not significantly differ from those in controls. Network characteristics correlated with clinical presentation regarding seizure frequency in LGG patients, and with poorer cognitive performance in both LGG and HGG glioma patients.ConclusionLesion histology partly determines differences in functional networks in glioma patients suffering from epilepsy. We suggest that differences between LGG and HGG patients' networks are explained by differences in plasticity, guided by the particular lesional growth pattern. Interestingly, decreased synchronizability and decreased global integration in the theta band seem to make LGG and NGL patients more prone to the occurrence of seizures and cognitive decline.

| S-EPMC3498183 | biostudies-literature

LOGGIC Core BioClinical Data Bank: Added clinical value of RNA-Seq in an international molecular diagnostic registry for pediatric low-grade glioma patients

Project description:We compared gene panel sequencing and DNA methylation analysis with RNA sequencing results from 125 patients. We could demonstrate improvement of diagnostic accuracy and clinical patient benefit by the addition of RNA sequencing fom fresh frozen tumor tissue.

2023-11-15 | GSE228100 | GEO

Survival after radiation therapy for high-grade glioma.

Project description:Background:High-grade gliomas (HGGs) are a heterogeneous disease group, with variable prognosis, inevitably causing deterioration of the quality of life. The estimated 2-year overall survival is 20%, despite the best trimodality treatment consisting of surgery, chemotherapy, and radiotherapy. Aim:To evaluate long-term survival outcomes and factors influencing the survival of patients with high-grade gliomas treated with radiotherapy. Materials and methods:Data from 47 patients diagnosed with high-grade gliomas between 2009 and 2014 and treated with three-dimensional radiotherapy (3DRT) or intensity-modulated radiotherapy (IMRT) were analyzed retrospectively. Results:Median survival was 16.6 months; 29 patients (62%) died before the time of analysis. IMRT was employed in 68% of cases. The mean duration of radiotherapy was 56 days, and the mean delay to the start of radiotherapy was 61.7 days (range, 27-123 days). There were no statistically significant effects of duration of radiotherapy or delay to the start of radiotherapy on patient outcomes. Conclusions:Age, total amount of gross resection, histological type, and use of adjuvant temozolomide influenced survival rate (p < 0.05). The estimated overall survival was 18 months (Kaplan-Meier estimator). Our results corroborated those reported in the literature.

| S-EPMC6187089 | biostudies-literature

Survival and low-grade glioma: the emergence of genetic information.

Project description:Significant gaps exist in our understanding of the causes and clinical management of glioma. One of the biggest gaps is how best to manage low-grade (World Health Organization [WHO] Grade II) glioma. Low-grade glioma (LGG) is a uniformly fatal disease of young adults (mean age 41 years), with survival averaging approximately 7 years. Although LGG patients have better survival than patients with high-grade (WHO Grade III or IV) glioma, all LGGs eventually progress to high-grade glioma and death. Data from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute suggest that for the majority of LGG patients, overall survival has not significantly improved over the past 3 decades, highlighting the need for intensified study of this tumor. Recently published research suggests that historically used clinical variables are not sufficient (and are likely inferior) prognostic and predictive indicators relative to information provided by recently discovered tumor markers (e.g., 1p/19q deletion and IDH1 or IDH2 mutation status), tumor expression profiles (e.g., the proneural profile) and/or constitutive genotype (e.g., rs55705857 on 8q24.21). Discovery of such tumor and constitutive variation may identify variables needed to improve randomization in clinical trials as well as identify patients more sensitive to current treatments and targets for improved treatment in the future. This article reports on survival trends for patients diagnosed with LGG within the United States from 1973 through 2011 and reviews the emerging role of tumor and constitutive genetics in refining risk stratification, defining targeted therapy, and improving survival for this group of relatively young patients.

| S-EPMC4361022 | biostudies-literature

Survival analysis of immune-related lncRNA in low-grade glioma.

Project description:BackgroundLow-grade glioma is grade I-II glioma. Immunotherapy is a promising way of tumor killing. Research on immune molecular mechanisms in low-grade gliomas and discovery of new immune checkpoints for low-grade gliomas are of great importance.MethodsGene sequencing data and clinical data of low-grade glioma were downloaded from TCGA database. Prognosis related lncRNAs were identified by Cox regression and their possible functions were found by gene enrichment set analysis.ResultsA total of 529 low-grade glioma samples and 5 non-tumor brain tissue samples are obtained from the TCGA database. Two hundred forty-seven immune-associated lncRNAs are screened. Cox regression showed that 16 immune-related lncRNAs are associated with low-grade glioma prognosis, and 7 lncRNAs are independent risk factors. Gene set enrichment analysis suggests that these molecules are enriched in extracellular region, sequence-specific DNA binding, neuropeptide signaling pathway, transcriptional misregulation in cancer, cytokine-cytokine receptor interaction, protein digestion and absorption, chemokine signaling pathway, etc. CONCLUSION: The identification of immune-related lncRNA may provide new targets for the research of the molecular mechanisms and treatment of low-grade glioma.

| S-EPMC6697914 | biostudies-literature

Multiparametric MRI texture analysis in prediction of glioma biomarker status: added value of MR diffusion.

Project description:BackgroundEarly identification of glioma molecular phenotypes can lead to understanding of patient prognosis and treatment guidance. We aimed to develop a multiparametric MRI texture analysis model using a combination of conventional and diffusion MRI to predict a wide range of biomarkers in patients with glioma.MethodsIn this retrospective study, patients were included if they (1) had diagnosis of gliomas with known IDH1, EGFR, MGMT, ATRX, TP53, and PTEN status from surgical pathology and (2) had preoperative MRI including FLAIR, T1c+ and diffusion for radiomic texture analysis. Statistical analysis included logistic regression and receiver-operating characteristic (ROC) curve analysis to determine the optimal model for predicting glioma biomarkers. A comparative analysis between ROCs (conventional only vs conventional + diffusion) was performed.ResultsFrom a total of 111 patients included, 91 (82%) were categorized to training and 20 (18%) to test datasets. Constructed cross-validated model using a combination of texture features from conventional and diffusion MRI resulted in overall AUC/accuracy of 1/79% for IDH1, 0.99/80% for ATRX, 0.79/67% for MGMT, and 0.77/66% for EGFR. The addition of diffusion data to conventional MRI features significantly (P < .05) increased predictive performance for IDH1, MGMT, and ATRX. The overall accuracy of the final model in predicting biomarkers in the test group was 80% (IDH1), 70% (ATRX), 70% (MGMT), and 75% (EGFR).ConclusionAddition of MR diffusion to conventional MRI features provides added diagnostic value in preoperative determination of IDH1, MGMT, and ATRX in patients with glioma.

| S-EPMC8156980 | biostudies-literature

Early toxicity predicts long-term survival in high-grade glioma.

Project description:BackgroundPatients with high-grade gliomas are treated with surgery followed by chemoradiation. The risk factors and implications of neurological side effects are not known.MethodsAcute and late ≥ grade 3 neurological toxicities (NTs) were analysed among 2761 patients from 14 RTOG trials accrued from 1983 to 2003. The association between acute and late toxicity was analysed using a stepwise logistic regression model. The association between the occurrence of acute NT and survival was analysed as an independent variable.ResultsThere were 2610 analysable patients (86% glioblastoma, 10% anaplastic astrocytoma). All received a systemic agent during radiation (83% chemotherapy, 17% biological agents). Median radiation dose was 60 Gy. There were 182 acute and 83 late NT events. On univariate analysis, older age, poor performance status, aggressive surgery, pre-existing neurological dysfunction, poor mental status and twice-daily radiation were associated with increased acute NT. In a stepwise logistic regression model the occurrence of acute NT was significantly associated with late NT (OR=2.40; 95% CI=1.2-4.8; P=0.014). The occurrence of acute NT predicted poorer overall survival, independent of recursive partitioning analysis class (median 7.8 vs 11.8 months).InterpretationAcute NT is significantly associated with both late NT and overall survival.

| S-EPMC3101937 | biostudies-literature

Survival and long-term health and cognitive outcomes after low-grade glioma.

Project description:Long-term morbidity for children with low-grade glioma (LGG) requires exposure-specific characterization. Overall survival (OS) and progression-free survival (PFS) were estimated for 361 children diagnosed with LGG between 1985 and 2007 at a single institution. Five-year survivors (n = 240) received risk-based clinical assessment. Cumulative incidence of late effects 15 years from diagnosis were estimated. Risk factors for adverse health were identified using Fine and Gray's approach to Cox's proportional hazards model, accounting for death as a competing risk. OS at 15 years was 86% (95% confidence interval [CI] 82%-90%), and PFS was 55% (95% CI 51%-58%). Among the 240 5-year survivors, the 5-, 10-, and 15-year cumulative incidence of adverse outcomes included blindness: 10%, 13%, and 18%, respectively; hearing loss: 8%, 14%, and 22%; obesity/overweight: 18%, 35%, and 53%; hyperinsulinism: 1%, 5%, and 24%; growth hormone deficiency: 13%, 27%, and 29%;thyroid hormone deficiency: 16%, 28%, and 33%; and adrenocorticotropic hormone (ACTH) deficiency: 12%, 22%, and 26%. Multivariable models demonstrated radiation therapy to be a significant independent predictor of hearing loss, growth hormone deficiency, abnormal thyroid function, and ACTH deficiency. Diencephalic location was a statistically significant independent risk factor for blindness, growth hormone deficiency, abnormal thyroid function, and ACTH deficiency. Among the 182 5-year survivors assessed for intellectual function, 34% had an intelligence quotient (IQ) below average (<85), associated with younger age at diagnosis, epilepsy, and shunt placement. Survivors of childhood LGG experience substantial long-term adverse effects that continue to increase well beyond the 5-year survival time point.

| S-EPMC3064628 | biostudies-literature

Low-grade glioma microglia

Project description:To examine the effect of Nf1 inactivation in astrocytes on normal microglia in the optic nerve, microglia from Nf1 flox/flox (FF) and Nf1 flox/flox; GFAP-Cre (FFC) were flow sorted. High throughput RNA-seq was employed to compare the expression profiles, and upregulated genes in microglia supportive to Nf1 deficient astrocytes were verified.

2020-07-03 | GSE65865 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data