ReviewOncotarget2026
Bibliometric mapping of glioma classification research through main path, key route, and K-core analyses.
Review in Oncotarget, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Copyright: © 2026 Ahmed and Núñez-Ríos. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Burgeoning technological and clinical advances have significantly reshaped glioma classification. To assess the evolution of these changes, we analyzed bibliometric data from Web of Science to explore patterns in the socio-clinical domains of glioma classification research. Using network analysis, we built a direct citation network linking articles to authors, focusing on citations. Main Path Analysis provided an overview of research evolution, Key Route Analysis identified influential papers, and K-core analysis revealed densely connected articles. The network comprised 46,204 nodes and 231,432 arcs, highlighting DNA methylation profiling’s role in advancing molecular biomarker-based classification models. KRA emphasized advanced imaging and molecular techniques as key drivers, while K-core analysis identified articles cited at least 19 times. The findings indicate that the subset of articles focusing on glioma classification that incorporate social factors is relatively scarce in the analyzed data, in contrast to the prominence of epigenetic and imaging factors in the literature. Unlike previous studies that focused primarily on metrics such as the h-index, our approach identifies the limited but notable mention of social factors in glioma classification research, thereby highlighting a thematic gap. Through quantitative network analysis complemented by narrative interpretation, we uncovered patterns and substructures that offer deep insights into the evolving research landscape.
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.