ArticleTranslational cancer research2025
Establishment and validation of a prognostic prediction model for glioma based on key genes and clinical factors.
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed.
- Construction and validation of a prognostic model for glioma: an analysis based on mismatch repair-related genes and their correlation with clinicopathological features.Translational cancer research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Glioma is a common brain tumour that is associated with poor prognosis. Immunotherapy has shown significant potential in the treatment of gliomas. Herein, we proposed a new prognostic risk model based on immune- and mitochondrial energy metabolism-related differentially expressed genes (IR&MEMRDEGs) to enhance the accuracy of prognostic assessment in patients with glioma. Methods: Data from samples from 671 glioma patients and 5 normal controls with available follow-up data and prognostic outcomes were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. All data were downloaded on 13 November 2023. IR&MEMRDEGs were screened from the GeneCards website and published literature. Prognostic prediction models were constructed and analysed using Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression, Kaplan-Meier (KM) curve, and receiver operating characteristic (ROC) curve analyses. Single-sample gene set enrichment analysis (ssGSEA) was further performed to ascertain the percentage of immune cell infiltration in the glioma specimens. Results: Bioinformatics analysis of the GEO and TCGA databases identified eleven MEMRDEGs with dysregulated expression in gliomas: Conclusions: The present study confirmed the significant predictive value of
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.