SynthesisNeurosurgical review2026
Impact of tumor treating fields on overall and progression-free survival in newly diagnosed glioblastoma: A systematic review and meta-analysis.
Synthesis in Neurosurgical review, 2026. 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
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
2 citing papers in PubMed.
- Review
- Integrating Molecular Pathology, Tumor Microenvironment, and Novel Therapies to Overcome Resistance in Glioblastoma.Journal of molecular neuroscience : MN · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma (GBM) remains the most aggressive primary brain tumor in adults, with median overall survival under two years despite maximal resection and chemoradiation. Tumor Treating Fields (TTFields) is a treatment modality that disrupts mitosis and inhibits tumor proliferation with low intensity, alternating electric fields. The landmark EF-14 trial demonstrated significant overall survival (OS) and progression-free survival (PFS) benefits with the addition of TTFields to temozolomide. However, the generalizability of these findings in broader, real-world settings is uncertain. This systematic review and meta-analysis evaluated the pooled impact of TTFields on OS and PFS in newly diagnosed GBM. A systematic search was conducted in PubMed, Embase, and Scopus through September 2025. All studies comparing standard Stupp protocol ± TTFields in newly diagnosed GBM. Outcomes of interest were OS and PFS. For OS and PFS, the pooled hazard ratio was estimated using a random-effects model. Heterogeneity of the effects across the studies was described by Cochran's Q and the I2 statistics. Twelve studies involving 2,761 patients (1,214 TTFields-treated; 1,547 controls) met the inclusion criteria, including one Phase III RCT and eleven retrospective or registry-based cohorts. Pooled analysis showed that TTFields significantly improved OS, HR = 0.68, 95% CI 0.60–0.78, p < 0.0001; I2 = 41%, and PFS, HR = 0.68, 95% CI 0.59–0.78, p < 0.0001; I2 = 48%. The mean PFS across these studies was 13.6 months with TTFields versus 9.0 months with standard therapy (+ 4.6-month improvement), while the mean OS was 23.5 months with TTFields versus 18.0 months with standard therapy (+ 5.5-month improvement). Benefit was consistent across age, resection extent, and MGMT promoter methylation subgroups. Skin irritation was the most frequent adverse event, with no systemic toxicity reported. The use of TTFields significantly prolongs both overall and PFS in newly diagnosed GBM patients, which has been reproducible in a series of randomized trials and real-world studies. These findings strongly support the adoption of TTFields as a standard adjuvant to temozolomide maintenance in the use of combinatorial approaches with immunotherapy and targeted agents.
Indexed as
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.