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Frontiers in Public Health 2024Progressive glioblastoma (GBM) is a malignancy with extremely poor prognosis. Chemotherapy is one of the approved systemic treatment modalities. The aim of this study is...
BACKGROUND
Progressive glioblastoma (GBM) is a malignancy with extremely poor prognosis. Chemotherapy is one of the approved systemic treatment modalities. The aim of this study is to assess the cost-effectiveness of using bevacizumab (BEV) in combination with lomustine (LOM) regimen for the treatment of progressive glioblastoma in China.
METHODS
The estimation results are derived from a multicenter randomized phase III trial, which demonstrated improved survival in GBM patients receiving BEV+LOM combination therapy. To calculate the incremental cost-effectiveness ratio (ICER) from the perspective of Chinese society, a Markov model was established. Univariate deterministic analysis and probabilistic sensitivity analysis were employed to address the uncertainties within the model.
RESULTS
Compared to LOM monotherapy, the total treatment cost for BEV+LOM combination therapy increased from $2,646.70 to $23,650.98. The health-adjusted life years (QALYs) for BEV+LOM combination therapy increased from 0.26 QALYs to 0.51 QALYs, representing an increment of 0.25 QALYs. The incremental cost-effectiveness ratio (ICER) was $84,071.12. The cost-effectiveness curve indicates that within the willingness-to-pay (WTP) range of $35,906 per QALY, BEV+LOM combination therapy is not a cost-effective treatment option for unresectable malignant pleural mesothelioma patients.
CONCLUSIONS
Taken as a whole, the findings of this study suggest that, from the perspective of payers in China, BEV+LOM combination therapy as a first-line treatment for GBM is not a cost-effective option. However, considering the survival advantages this regimen may offer for this rare disease, it may still be one of the clinical treatment options for this patient population.
Topics: Bevacizumab; Glioblastoma; Humans; Cost-Benefit Analysis; Lomustine; Markov Chains; China; Antineoplastic Combined Chemotherapy Protocols; Quality-Adjusted Life Years; Brain Neoplasms; Cost-Effectiveness Analysis
PubMed: 38883194
DOI: 10.3389/fpubh.2024.1410355 -
International Journal of Nanomedicine 2024Patients diagnosed with glioma typically face a limited life expectancy (around 15 months on average), a bleak prognosis, and a high likelihood of recurrence. As such,... (Review)
Review
Patients diagnosed with glioma typically face a limited life expectancy (around 15 months on average), a bleak prognosis, and a high likelihood of recurrence. As such, glioma is recognized as a significant form of malignancy. Presently, the treatment options for glioma include traditional approaches such as surgery, chemotherapy, and radiotherapy. Regrettably, the efficacy of these treatments has been less than optimal. Nevertheless, a promising development in glioma treatment lies in the use of hydrogel nano-systems as sophisticated delivery systems. These nano-systems have demonstrated exceptional therapeutic effects in the treatment of glioma by various responsive ways, including temperature-response, pH-response, liposome-response, ROS-response, light-response, and enzyme-response. This study seeks to provide a comprehensive summary of both the therapeutic application of hydrogel nano-systems in managing glioma and the underlying immune action mechanisms.
Topics: Glioma; Humans; Hydrogels; Brain Neoplasms; Animals; Liposomes; Drug Delivery Systems; Nanomedicine; Nanoparticles
PubMed: 38882547
DOI: 10.2147/IJN.S470315 -
BMC Cancer Jun 2024Glioblastoma (GBM) is the most common and aggressive primary brain cancer. The treatment of GBM consists of a combination of surgery and subsequent oncological therapy,... (Clinical Trial)
Clinical Trial
BACKGROUND
Glioblastoma (GBM) is the most common and aggressive primary brain cancer. The treatment of GBM consists of a combination of surgery and subsequent oncological therapy, i.e., radiotherapy, chemotherapy, or their combination. If postoperative oncological therapy involves irradiation, magnetic resonance imaging (MRI) is used for radiotherapy treatment planning. Unfortunately, in some cases, a very early worsening (progression) or return (recurrence) of the disease is observed several weeks after the surgery and is called rapid early progression (REP). Radiotherapy planning is currently based on MRI for target volumes definitions in many radiotherapy facilities. However, patients with REP may benefit from targeting radiotherapy with other imaging modalities. The purpose of the presented clinical trial is to evaluate the utility of C-methionine in optimizing radiotherapy for glioblastoma patients with REP.
METHODS
This study is a nonrandomized, open-label, parallel-setting, prospective, monocentric clinical trial. The main aim of this study was to refine the diagnosis in patients with GBM with REP and to optimize subsequent radiotherapy planning. Glioblastoma patients who develop REP within approximately 6 weeks after surgery will undergo C-methionine positron emission tomography (PET/CT) examinations. Target volumes for radiotherapy are defined using both standard planning T1-weighted contrast-enhanced MRI and PET/CT. The primary outcome is progression-free survival defined using RANO criteria and compared to a historical cohort with REP treated without PET/CT optimization of radiotherapy.
DISCUSSION
PET is one of the most modern methods of molecular imaging. C-Methionine is an example of a radiolabelled (carbon 11) amino acid commonly used in the diagnosis of brain tumors and in the evaluation of response to treatment. Optimized radiotherapy may also have the potential to cover those regions with a high risk of subsequent progression, which would not be identified using standard-of-care MRI for radiotherapy planning. This is one of the first study focused on radiotherapy optimization for subgroup of patinets with REP.
TRIAL REGISTRATION
NCT05608395, registered on 8.11.2022 in clinicaltrials.gov; EudraCT Number: 2020-000640-64, registered on 26.5.2020 in clinicaltrialsregister.eu. Protocol ID: MOU-2020-01, version 3.2, date 18.09.2020.
Topics: Adult; Aged; Female; Humans; Male; Middle Aged; Brain Neoplasms; Carbon Radioisotopes; Disease Progression; Glioblastoma; Magnetic Resonance Imaging; Methionine; Positron Emission Tomography Computed Tomography; Prospective Studies; Radiopharmaceuticals; Radiotherapy Planning, Computer-Assisted
PubMed: 38879476
DOI: 10.1186/s12885-024-12469-2 -
Clinical and Translational Medicine Jun 2024
Topics: Neuroblastoma; Humans; Anaplastic Lymphoma Kinase; Protein Kinase Inhibitors; Immunotherapy, Adoptive
PubMed: 38877641
DOI: 10.1002/ctm2.1732 -
Acta Neuropathologica Communications Jun 2024MYC dysregulation is pivotal in the onset and progression of IDH-mutant gliomas, mostly driven by copy-number alterations, regulatory element alterations, or epigenetic...
MYC dysregulation is pivotal in the onset and progression of IDH-mutant gliomas, mostly driven by copy-number alterations, regulatory element alterations, or epigenetic changes. Our pilot analysis uncovered instances of relative MYC overexpression without alterations in the proximal MYC network (PMN), prompting a deeper investigation into potential novel oncogenic mechanisms. Analysing comprehensive genomics profiles of 236 "IDH-mutant 1p/19q non-co-deleted" lower-grade gliomas from The Cancer Genome Atlas, we identified somatic genomic alterations within the PMN. In tumours without PMN-alterations but with MYC-overexpression, genes correlated with MYC-overexpression were identified. Our analyses yielded that 86/236 of astrocytomas exhibited no PMN-alterations, a subset of 21/86 displaying relative MYC overexpression. Within this subset, we discovered 42 genes inversely correlated with relative MYC expression, all on 19q. Further analysis pinpointed a minimal common region at 19q13.43, encompassing 15 genes. The inverse correlations of these 15 genes with relative MYC overexpression were re-confirmed using independent scRNAseq data. Further, the micro-deleted astrocytoma subset displayed significantly higher genomic instability compared to WT cases, but lower instability compared to PMN-hit cases. This newly identified 19q micro-deletion represents a potential novel mechanism underlying MYC dysregulation in astrocytomas. Given the prominence of 19q loss in IDH-mutant gliomas, our findings bear significant implications for understanding gliomagenesis.
Topics: Humans; Isocitrate Dehydrogenase; Astrocytoma; Brain Neoplasms; Proto-Oncogene Proteins c-myc; Chromosomes, Human, Pair 19; Chromosome Deletion; Mutation
PubMed: 38877600
DOI: 10.1186/s40478-024-01811-1 -
BMC Neurology Jun 2024Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient...
BACKGROUND
Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management.
METHODS
Integrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications.
RESULTS
457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups.
CONCLUSIONS
Glioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage.
Topics: Humans; Male; Female; Glioma; Middle Aged; Retrospective Studies; Prognosis; Adult; Brain Neoplasms; Aged; Cohort Studies; Young Adult
PubMed: 38877400
DOI: 10.1186/s12883-024-03703-2 -
CNS Oncology Dec 2024Glioneuronal and neuronal tumors are rare primary central nervous system malignancies with heterogeneous features. Due to the rarity of these malignancies diagnosis and... (Review)
Review
Glioneuronal and neuronal tumors are rare primary central nervous system malignancies with heterogeneous features. Due to the rarity of these malignancies diagnosis and treatment remains a clinical challenge. Here we performed a narrative review aimed to investigate the principal issues concerning the diagnosis, pathology, and clinical management of glioneuronal tumors. Diagnostic criteria have been recently overturned thanks to a better characterization on a histological and molecular biology level. The study of genomic alterations occurring within these tumors has allowed us to identify potential therapeutic targets including BRAF, FGFR, and PDGFRA. Techniques allowing molecular sequencing DNA methylation assessment of the disease are essential diagnostic tools. Targeting agents should be included in the therapeutic armamentarium after loco-regional treatment failure.
Topics: Humans; Young Adult; Brain Neoplasms; Central Nervous System Neoplasms; Glioma
PubMed: 38873961
DOI: 10.1080/20450907.2024.2357532 -
Mathematical Biosciences and... Apr 2024
Topics: Glioblastoma; Humans; Cell Proliferation; Brain Neoplasms
PubMed: 38872553
DOI: 10.3934/mbe.2024250 -
Mathematical Biosciences and... Mar 2024The increasing global incidence of glioma tumors has raised significant healthcare concerns due to their high mortality rates. Traditionally, tumor diagnosis relies on...
The increasing global incidence of glioma tumors has raised significant healthcare concerns due to their high mortality rates. Traditionally, tumor diagnosis relies on visual analysis of medical imaging and invasive biopsies for precise grading. As an alternative, computer-assisted methods, particularly deep convolutional neural networks (DCNNs), have gained traction. This research paper explores the recent advancements in DCNNs for glioma grading using brain magnetic resonance images (MRIs) from 2015 to 2023. The study evaluated various DCNN architectures and their performance, revealing remarkable results with models such as hybrid and ensemble based DCNNs achieving accuracy levels of up to 98.91%. However, challenges persisted in the form of limited datasets, lack of external validation, and variations in grading formulations across diverse literature sources. Addressing these challenges through expanding datasets, conducting external validation, and standardizing grading formulations can enhance the performance and reliability of DCNNs in glioma grading, thereby advancing brain tumor classification and extending its applications to other neurological disorders.
Topics: Humans; Glioma; Magnetic Resonance Imaging; Brain Neoplasms; Neoplasm Grading; Neural Networks, Computer; Reproducibility of Results; Deep Learning; Algorithms; Brain; Image Processing, Computer-Assisted; Image Interpretation, Computer-Assisted
PubMed: 38872535
DOI: 10.3934/mbe.2024232 -
Scientific Reports Jun 2024Prediction of glioma is crucial to provide a precise treatment plan to optimize the prognosis of children with glioma. However, studies on the grading of pediatric...
Prediction of glioma is crucial to provide a precise treatment plan to optimize the prognosis of children with glioma. However, studies on the grading of pediatric gliomas using radiomics are limited. Meanwhile, existing methods are mainly based on only radiomics features, ignoring intuitive information about tumor morphology on traditional imaging features. This study aims to utilize multiparametric magnetic resonance imaging (MRI) to identify high-grade and low-grade gliomas in children and establish a classification model based on radiomics features and clinical features. A total of 85 children with gliomas underwent tumor resection, and part of the tumor tissue was examined pathologically. Patients were categorized into high-grade and low-grade groups according to World Health Organization guidelines. Preoperative multiparametric MRI data, including contrast-enhanced T1-weighted imaging, T2-weighted imaging, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted images, and apparent diffusion coefficient sequences, were obtained and labeled by two radiologists. The images were preprocessed, and radiomics features were extracted for each MRI sequence. Feature selection methods were used to select radiomics features, and statistically significant clinical features were identified using t-tests. The selected radiomics features and conventional MRI features were used to train the AutoGluon models. The improved model, based on radiomics features and conventional MRI features, achieved a balanced classification accuracy of 66.59%. The cross-validated areas under the receiver operating characteristic curve for the classifier of AutoGluon frame were 0.8071 on the test dataset. The results indicate that the performance of AutoGluon models can be improved by incorporating conventional MRI features, highlighting the importance of the experience of radiologists in accurately grading pediatric gliomas. This method can help predict the grade of pediatric glioma before pathological examination and assist in determining the appropriate treatment plan, including radiotherapy, chemotherapy, drugs, and gene surgery.
Topics: Humans; Glioma; Child; Female; Male; Neoplasm Grading; Child, Preschool; Brain Neoplasms; Adolescent; Magnetic Resonance Imaging; Multiparametric Magnetic Resonance Imaging; Infant; ROC Curve; Radiomics
PubMed: 38871755
DOI: 10.1038/s41598-024-63222-5