Relationship between preoperative plasma fibrinogen and prognosis in patients with non-metastatic gastric cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Preoperative plasma fibrinogen (Fib) is a potential prognostic marker for various cancers, including gastric cancer. This systematic review and meta-analysis aimed to investigate the relationship between preoperative fibrinogen levels and prognosis in patients with non-metastatic gastric cancer patients. Methods: This meta-analysis was conducted in accordance with the PRISMA guidelines. A comprehensive literature search of PubMed, Embase, Web of Science, and Cochrane Library was performed up to May 26, 2025, without language or date restrictions. Eligible studies reported multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival (OS) and recurrence-free survival (RFS) in relation to preoperative fibrinogen levels. Subgroup and sensitivity analyses were performed, and study quality was assessed using the Newcastle-Ottawa Scale (NOS). Results: A total of 8 retrospective studies involving 4,281 patients were included. Pooled analysis revealed that elevated fibrinogen levels were significantly associated with poorer OS (HR = 1.56, 95% CI: 1.20-1.93, P < 0.001; I² = 57.0%) and RFS (HR = 2.08, 95% CI: 1.33-2.82, P < 0.001; I² = 0%). Subgroup analyses confirmed consistent associations across age, sex, tumor stage, geographic region, and fibrinogen cut-off values. No significant publication bias was detected. Conclusions: Elevated preoperative fibrinogen levels are significantly associated with worse overall and recurrence-free survival in patients with non-metastatic gastric cancer, indicating its potential utility as a prognostic biomarker. Given the limited data on RFS, further large-scale prospective studies are needed to validate these findings and support its integration into individualized risk stratification models.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".