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Record W4416810806 · doi:10.1186/s12885-025-15404-1

Prognostic impact of Fusobacterium nucleatum in head and neck cancers: a meta-analysis of critical oncological outcomes

2025· article· en· W4416810806 on OpenAlexaboutno aff
Asuman Feda Bayrak, Mehmet Emin Arayıcı, Özden Savaş, Erdoğan Özgür, Ayşe Aydan Özkütük, Enis Alpin Güneri̇

Bibliographic record

VenueBMC Cancer · 2025
Typearticle
Languageen
FieldMedicine
TopicOtolaryngology and Infectious Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsFusobacterium nucleatumFusobacteriumHead and neckSurgical oncologyFusobacteriaProspective cohort studyStage (stratigraphy)

Abstract

fetched live from OpenAlex

BACKGROUND: It's a well-established fact that Fusobacterium nucleatum has been implicated in the pathogenesis and prognosis of several malignancies, but its role in head and neck cancers remains unclear. This systematic review and meta-analysis aimed to synthesize the evidence on the prognostic impact of Fusobacterium abundance in head and neck squamous cell carcinoma (HNSCC). METHODS: A comprehensive literature search of PubMed/MEDLINE, Web of Science, Scopus, and Embase was performed from inception to January 1, 2000, to October 15, 2025. Studies evaluating the association between Fusobacterium and oncological outcomes in HNSCC were included. Hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and disease-specific survival (DSS) were pooled using random and fixed-effects models. Methodological quality was assessed with the Newcastle-Ottawa Scale (NOS), and reporting adhered to the PRISMA 2020 guidelines. The study protocol was prospectively registered in INPLASY (Registration ID: INPLASY2025110054). RESULTS: A total of six studies met the inclusion criteria, and five studies were included in the quantitative synthesis. The pooled analysis demonstrated a significant association between high Fusobacterium abundance and improved OS (random-effects model: HR = 0.60; 95% CI: 0.38-0.95, p = 0.03; I² = 37.6%; fixed-effects model: HR = 0.61; 95% CI: 0.43-0.87, p = 0.01; I² = 40.2%) and DSS (random-effects model: HR = 0.34; 95% CI: 0.19-0.61, p < 0.001; I² = 41.6%,; fixed-effects model: HR = 0.37; 95% CI: 0.24-0.56, p < 0.001; I² = 40.1%) in patients with HNSCC. Heterogeneity was low-to-moderate, and no significant small study effect was detected based on funnel plot inspection. CONCLUSIONS: This meta-analysis suggests that Fusobacterium nucleatum abundance is significantly associated with better OS and DSS in patients with head and neck cancers. Fusobacterium nucleatum may be a potentially useful prognostic biomarker; however, this interpretation should be made with caution due to the limited evidence base, small number of studies, and residual heterogeneity. Taken together, further validation in large-scale, prospective studies is required and critical.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.430
Teacher spread0.363 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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