ReviewBrain sciences2026
Evolving Landscape of Glioblastoma Research: Integrating Therapeutic Advances and Diagnostic Frontiers.
Review in Brain sciences, 2026. 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.
- Decoding and Overcoming Temozolomide Resistance Through CRISPR/Cas Technologies.Molecular diagnosis & therapy · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma (GB) remains the most aggressive primary brain malignancy, with the Stupp regimen persisting as the standard of care for nearly two decades despite poor survival outcomes. This review was synthesized by extensively reviewing and analyzing the literature from PubMed, Scopus, and Web of Science to evaluate the emerging promising therapeutic and diagnostic strategies for combating GB. Results indicate significant progress in molecularly targeted therapies, biomimetic nanocarriers, and advanced radiotherapy. While immunotherapeutic approaches, such as checkpoint inhibitors and vaccines, show variable clinical success, the integration of bioinformatics and machine learning has significantly enhanced treatment response prediction. Furthermore, advances in radiomics and molecular imaging have improved the differentiation between true tumor progression and pseudoprogression, potentially reducing invasive diagnostic requirements. Additionally, other emerging and investigational adjuvant therapeutic approaches have shown promise. We conclude that, while multimodal strategies integrating molecular and computational approaches offer a path toward personalized GB management, significant barriers-namely tumor heterogeneity and the blood-brain barrier-persist. Future research must prioritize precision-based combinatorial models to successfully translate these preclinical advancements into improved clinical outcomes for patients.
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What OpenQuestion 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 OpenQuestion graph.