Dataset Information

Molecular Biomarkers in Glioblastoma: A Systematic Review and Meta-Analysis.

ABSTRACT:

Background

Glioblastoma (GBM) is a highly aggressive cancer with poor prognosis that needs better treatment modalities. Moreover, there is a lack of reliable biomarkers to predict the response and outcome of current or newly designed therapies. While several molecular markers have been proposed as potential biomarkers for GBM, their uptake into clinical settings is slow and impeded by marker heterogeneity. Detailed assessment of prognostic and predictive value for biomarkers in well-defined clinical trial settings, if available, is scattered throughout the literature. Here we conducted a systematic review and meta-analysis to evaluate the prognostic and predictive significance of clinically relevant molecular biomarkers in GBM patients.

Material and methods

A comprehensive literature search was conducted to retrieve publications from 3 databases (Pubmed, Cochrane and Embase) from January 2010 to December 2021, using specific terms. The combined hazard ratios (HR) and confidence intervals (95% CI) were used to evaluate the association of biomarkers with overall survival (OS) in GBM patients.

Results

Twenty-six out of 1831 screened articles were included in this review. Nineteen articles were included in the meta-analyses, and 7 articles were quantitatively summarised. Fourteen studies with 1231 GBM patients showed a significant association of MGMT methylation with better OS with the pooled HR of 1.66 (95% CI 1.32-2.09, p < 0.0001, random effect). Five studies including 541 GBM patients analysed for the prognostic significance of IDH1 mutation showed significantly better OS in patients with IDH1 mutation with a pooled HR of 2.37 (95% CI 1.81-3.12; p < 0.00001]. Meta-analysis performed on 5 studies including 575 GBM patients presenting with either amplification or high expression of EGFR gene did not reveal any prognostic significance with a pooled HR of 1.31 (95% CI 0.96-1.79; p = 0.08).

Conclusions

MGMT promoter methylation and IDH1 mutation are significantly associated with better OS in GBM patients. No significant associations were found between EGFR amplification or overexpression with OS.

SUBMITTER: Sareen H

PROVIDER: S-EPMC9408540 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular Biomarkers in Glioblastoma: A Systematic Review and Meta-Analysis.

Sareen Heena H Ma Yafeng Y Becker Therese M TM Roberts Tara L TL de Souza Paul P Powter Branka B

International journal of molecular sciences 20220809 16

Background: Glioblastoma (GBM) is a highly aggressive cancer with poor prognosis that needs better treatment modalities. Moreover, there is a lack of reliable biomarkers to predict the response and outcome of current or newly designed therapies. While several molecular markers have been proposed as potential biomarkers for GBM, their uptake into clinical settings is slow and impeded by marker heterogeneity. Detailed assessment of prognostic and predictive value for biomarkers in well-defined cli ...[more]

PMID: 36012105

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Project description:ObjectiveMonitoring biomarkers using machine learning (ML) may determine glioblastoma treatment response. We systematically reviewed quality and performance accuracy of recently published studies.MethodsFollowing Preferred Reporting Items for Systematic Reviews and Meta-Analysis: Diagnostic Test Accuracy, we extracted articles from MEDLINE, EMBASE and Cochrane Register between 09/2018-01/2021. Included study participants were adults with glioblastoma having undergone standard treatment (maximal resection, radiotherapy with concomitant and adjuvant temozolomide), and follow-up imaging to determine treatment response status (specifically, distinguishing progression/recurrence from progression/recurrence mimics, the target condition). Using Quality Assessment of Diagnostic Accuracy Studies Two/Checklist for Artificial Intelligence in Medical Imaging, we assessed bias risk and applicability concerns. We determined test set performance accuracy (sensitivity, specificity, precision, F1-score, balanced accuracy). We used a bivariate random-effect model to determine pooled sensitivity, specificity, area-under the receiver operator characteristic curve (ROC-AUC). Pooled measures of balanced accuracy, positive/negative likelihood ratios (PLR/NLR) and diagnostic odds ratio (DOR) were calculated. PROSPERO registered (CRD42021261965).ResultsEighteen studies were included (1335/384 patients for training/testing respectively). Small patient numbers, high bias risk, applicability concerns (particularly confounding in reference standard and patient selection) and low level of evidence, allow limited conclusions from studies. Ten studies (10/18, 56%) included in meta-analysis gave 0.769 (0.649-0.858) sensitivity [pooled (95% CI)]; 0.648 (0.749-0.532) specificity; 0.706 (0.623-0.779) balanced accuracy; 2.220 (1.560-3.140) PLR; 0.366 (0.213-0.572) NLR; 6.670 (2.800-13.500) DOR; 0.765 ROC-AUC.ConclusionML models using MRI features to distinguish between progression and mimics appear to demonstrate good diagnostic performance. However, study quality and design require improvement.

Project description:ContextProstate cancer (PCa) is the second most common type of cancer in men. Individualized risk stratification is crucial to adjust decision-making. A variety of molecular biomarkers have been developed in order to identify patients at risk of clinically significant PCa (csPCa) defined by the most common PCa risk stratification systems.ObjectiveThe present study aims to examine the effectiveness (diagnostic accuracy) of blood or urine-based PCa biomarkers to identify patients at high risk of csPCa.Evidence acquisitionA systematic review of the literature was conducted. Medline and EMBASE were searched from inception to March 2021. Randomized or nonrandomized clinical trials, and cohort and case-control studies were eligible for inclusion. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Pooled estimates of sensitivity, specificity, and area under the curve were obtained.Evidence synthesisSixty-five studies (N = 34 287) were included. Not all studies included prostate-specific antigen-selected patients. The pooled data showed that the Prostate Health Index (PHI), with any cutoff point between 15 and 30, had sensitivity of 0.95-1.00 and specificity of 0.14-0.33 for csPCa detection. The pooled estimates for SelectMDx test sensitivity and specificity were 0.84 and 0.49, respectively.ConclusionsThe PHI test has a high diagnostic accuracy rate for csPCa detection, and its incorporation in the diagnostic process could reduce unnecessary biopsies. However, there is a lack of evidence on patient-important outcomes and thus more research is needed.Patient summaryIt has been possible to verify that the application of biomarkers could help detect prostate cancer (PCa) patients with a higher risk of poorer evolution. The Prostate Health Index shows an ability to identify 95-100 for every 100 patients suffering from clinically significant PCa who take the test, preventing unnecessary biopsies in 14-33% of men without PCa or insignificant PCa.

Project description:BackgroundGlioblastoma multiforme (GBM) has a poor prognosis despite a multi modal treatment that includes normofractionated radiotherapy. So, various hypofractionated alternatives to normofractionated RT have been tested to improve such prognosis. There is need of systematic review and meta-analysis to analyse the literature properly and maybe generalised the use of hypofractionation. The aim of this study was first, to perform a meta-analysis of all controlled trials testing the impact of hypofractionation on survival without age restriction and secondly, to analyse data from all non-comparative trials testing the impact of hypofractionation, radiosurgery and hypofractionated stereotactic RT in first line.Materials/methodsWe searched Medline, Embase and Cochrane databases to identify all publications testing the impact of hypofractionation in glioblastoma between 1985 and March 2020. Combined hazard ratio from comparative studies was calculated for overall survival. The impact of study design, age and use of adjuvant temozolomide was explored by stratification. Meta-regressions were performed to determine the impact of prognostic factors.Results2283 publications were identified. Eleven comparative trials were included. No impact on overall survival was evidenced (HR: 1.07, 95%CI: 0.89-1.28) without age restriction. The analysis of non-comparative literature revealed heterogeneous outcomes with limited quality of reporting. Concurrent chemotherapy, completion of surgery, immobilization device, isodose of prescription, and prescribed dose (depending on tumour volume) were poorly described. However, results on survival are encouraging and were correlated with the percentage of resected patients and with patients age but not with median dose.ConclusionsBecause few trials were randomized and because the limited quality of reporting, it is difficult to define the place of hypofactionation in glioblastoma. In first line, hypofractionation resulted in comparable survival outcome with the benefit of a shortened duration. The method used to assess hypofractionation needs to be improved.

Project description:IntroductionPsoriatic arthritis (PsA) is a chronic inflammatory disease that frequently develops in patients with psoriasis (PsO) but can also occur spontaneously. As a result, PsA diagnosis and treatment is commonly delayed, or even missed outright due to the manifold of clinical presentations that patients often experience. This inevitably results in progressive articular damage to axial and peripheral joints and entheses. As such, patients with PsA frequently experience reduced expectancy and quality of life due to disability. More recently, research has aimed to improve PsA diagnosis and prognosis by identifying novel disease biomarkers.MethodsHere, we conducted a systematic review of the published literature on candidate biomarkers for PsA diagnosis and prognosis in MEDLINE(Pubmed), EMBase and the Cochrane library with the goal to identify clinically applicable PsA biomarkers. Meta-analyses were performed when a diagnostic bone and cartilage turnover biomarker was reported in 2 or moredifferent cohorts of PsA and control.ResultsWe identified 1444 publications and 124 studies met eligibility criteria. We highlighted bone and cartilage turnover biomarkers, genetic markers, and autoantibodies used for diagnostic purposes of PsA, as well as acute phase reactant markers and bone and cartilage turnover biomarkers for activity or prognostic severity purposes. Serum cartilage oligometrix metalloproteinase levels were significantly increased in the PsA sera compared to Healthy Control (HC) with a standardized mean difference (SMD) of 2.305 (95%CI 0.795-3.816, p=0.003) and compared to osteoarthritis (OA) with a SMD of 0.783 (95%CI 0.015-1.551, p=0.046). The pooled serum MMP-3 levels were significantly higher in PsA patients than in PsO patients with a SMD of 0.419 (95%CI 0.119-0.719; p=0.006), but no significant difference was highlighted when PsA were compared to HC. While we did not identify any new genetic biomarkers that would be useful in the diagnosis of PsA, recent data with autoantibodies appear to be promising in diagnosis, but no replication studies have been published.ConclusionIn summary, no specific diagnostic biomarkers for PsA were identified and further studies are needed to assess the performance of potential biomarkers that can distinguish PsA from OA and other chronic inflammatory diseases.

Project description:ObjectiveTo systematically investigate the relationship between cardiac biomarkers and COVID-19 severity and mortality.MethodsWe performed a literature search using PubMed, Web of Science, and Google Scholar. The standardized mean difference (SMD) and 95% confidence interval (CI) were applied to estimate the combined results of 67 studies. A meta-analysis of cardiac biomarkers was used to evaluate disease mortality and severity in COVID-19 patients.ResultsA meta-analysis of 7812 patients revealed that patients with high levels of cardiac troponin I (SMD = 0.81 U/L, 95% CI = 0.14-1.48, P = 0.017), cardiac troponin T (SMD = 0.78 U/L, 95% CI = 0.07-1.49, P = 0.032), high-sensitive cardiac troponin I (SMD = 0.66 pg/mL, 95% CI = 0.51-0.81, P < 0.001), high-sensitive cardiac troponin T (SMD = 0.93 U/L, 95% CI = 0.21-1.65, P = 0.012), creatine kinase-MB (SMD = 0.54 U/L, 95% CI = 0.39-0.69, P < 0.001), and myoglobin (SMD = 0.80 U/L, 95% CI = 0.57-1.03, P < 0.001) were associated with prominent disease severity in COVID-19 infection. Moreover, 9532 patients with a higher serum level of cardiac troponin I (SMD = 0.51 U/L, 95% CI = 0.37-0.64, P < 0.001), high-sensitive cardiac troponin (SMD = 0.51 ng/L, 95% CI = 0.29-0.73, P < 0.001), high-sensitive cardiac troponin I (SMD = 0.51 pg/mL, 95% CI = 0.38-0.63, P < 0.001), high-sensitive cardiac troponin T (SMD = 0.85 U/L, 95% CI = 0.63-1.07, P < 0.001), creatine kinase-MB (SMD = 0.48 U/L, 95% CI = 0.32-0.65, P < 0.001), and myoglobin (SMD = 0.55 U/L, 95% CI = 0.45-0.65, P < 0.001) exhibited a prominent level of mortality from COVID-19 infection.ConclusionCardiac biomarkers (cardiac troponin I, cardiac troponin T, high-sensitive cardiac troponin, high-sensitive cardiac troponin I, high-sensitive cardiac troponin T, creatine kinase-MB, and myoglobin) should be more frequently applied in identifying high-risk COVID-19 patients so that timely treatment can be implemented to reduce severity and mortality in COVID-19 patients.

Dataset Information

Molecular Biomarkers in Glioblastoma: A Systematic Review and Meta-Analysis.

Background

Material and methods

Results

Conclusions

Publications

Molecular Biomarkers in Glioblastoma: A Systematic Review and Meta-Analysis.

Similar Datasets

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