Prognostic impact of Fusobacterium nucleatum in head and neck cancers: a meta-analysis of critical oncological outcomes
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.061 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".