ArticleSurgical neurology international2024
Optimizing glioblastoma treatment: A systematic review and meta-analysis of local injection and systemic drug delivery system in murine models.
Article in Surgical neurology international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Synergic microRNAs suppress human glioblastoma progression by modulating clinically relevant targets.Molecular therapy. Nucleic acids · 2025Article
- Emerging nanoplatforms towards microenvironment-responsive glioma therapy.Medical oncology (Northwood, London, England) · 2025Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Glioblastoma (GBM) is an aggressive primary brain tumor with a poor prognosis. The current gold standard for GBM treatment, known as the Stupp protocol, includes maximal safe surgical resection followed by radiotherapy and temozolomide chemotherapy. Despite extending survival modestly, this regimen is associated with significant side effects and limited efficacy, resulting in a median survival (MS) of 15 months and a 5-year survival rate of only 7%. A major challenge in GBM treatment is the blood-brain barrier (BBB), which restricts the penetration of therapeutic agents into the brain, thereby limiting the effectiveness of systemic therapies. To address these limitations, this systematic review and meta-analysis investigated the effectiveness of injectable local drug delivery systems (DDS) compared to systemic DDS in murine GBM models. This study aimed to provide robust evidence supporting the potential benefits of injectable local DDS for GBM treatment. Methods: A comprehensive literature search was conducted using PubMed, Embase, and ScienceDirect databases. The studies included were original research on local DDS of anticancer agents compared to systemic DDS in orthotopic GBM tumor models. The data extraction process included information on survival rates, tumor growth, and other relevant outcomes. Statistical analysis was performed using Review Manager 5.4, employing a random-effects model to calculate the pooled mean difference (MD) in survival time between local and systemic DDS. Results: Out of 1341 records, six studies met the inclusion criteria, totaling 129 murine models. The meta-analysis revealed that local injection of DDS significantly improved the MS compared to systemic administration (MD = 2.76; 95% confidence interval, 0.43-5.09; Conclusion: This systematic review and meta-analysis provide compelling evidence that local injection of DDS significantly improves survival in GBM models compared with systemic therapies. These findings highlight the potential of local DDS to overcome the challenges posed by the BBB and deliver higher concentrations of therapeutic agents directly to the tumor site. However, further research is needed to validate these findings in human clinical trials and refine DDS formulations. Future research should focus on developing DDS formulations capable of delivering multiple therapeutic agents simultaneously, addressing the experimental variability in preclinical models, and conducting rigorous clinical trials to evaluate the safety and efficacy of local DDS in human patients. Standardizing the testing methods across studies will facilitate more accurate comparisons and data integration, ultimately advancing the clinical translation of this promising therapeutic approach.
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