ReviewJournal of oncology2021
Promoting Prognostic Model Application: A Review Based on Gliomas.
Review in Journal of oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Prognostic and predictive impact of abnormal signal volume evolution early after chemoradiotherapy in glioblastoma.Journal of neuro-oncology · 2023Trial
- Contrastive multimodal deep learning for survival prediction in grade 2/3 gliomas.JNCI cancer spectrum · 2026Article
- Exploring the role of Disulfidptosis in glioma progression: insights into tumor heterogeneity and therapeutic potential through single-cell RNA sequencing.Discover oncology · 2024Article
- Identification of Key Immune and Cell Cycle Modules and Prognostic Genes for Glioma Patients through Transcriptome Analysis.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Identification of prognostic risk score of disulfidptosis-related genes and molecular subtypes in glioma.Biochemistry and biophysics reports · 2024Article
- Identification of the Roles of Coagulation-related Signature and its Key Factor RABIF in Hepatoma Cell Malignancy.Recent patents on anti-cancer drug discovery · 2024Article
- Article
- Glioblastoma glycolytic signature predicts unfavorable prognosis, immunological heterogeneity, and ENO1 promotes microglia M2 polarization and cancer cell malignancy.Cancer gene therapy · 2023Article
- Immune-related matrisomes are potential biomarkers to predict the prognosis and immune microenvironment of glioma patients.FEBS open bio · 2023Article
- Application of ATAC-seq in tumor-specific T cell exhaustion.Cancer gene therapy · 2023Review
- Development of prognostic indicator based on NAD+ metabolism related genes in glioma.Frontiers in surgery · 2023Article
- Pan-cancer and single-cell analysis reveal the prognostic value and immune response of NQO1.Frontiers in cell and developmental biology · 2023Article
- Article
- Characterization of aging tumor microenvironment with drawing implications in predicting the prognosis and immunotherapy response in low-grade gliomas.Scientific reports · 2022Article
- Large-Scale Single-Cell and Bulk Sequencing Analyses Reveal the Prognostic Value and Immune Aspects of CD147 in Pan-Cancer.Frontiers in immunology · 2022Article
- Article
- The construction of a hypoxia-based signature identified CA12 as a risk gene affecting uveal melanoma cell malignant phenotypes and immune checkpoint expression.Frontiers in oncology · 2022Article
- Identification of a Hypoxia-Angiogenesis lncRNA Signature Participating in Immunosuppression in Gastric Cancer.Journal of immunology research · 2022Article
- Identification of an Inflammatory Response-Related Gene Signature to Predict Survival and Immune Status in Glioma Patients.Journal of immunology research · 2022Article
- Transcriptional Patterns of Lower-Grade Glioma Patients with Distinct Ferroptosis Levels, Immunotherapy Response, and Temozolomide Sensitivity.Oxidative medicine and cellular longevity · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.