Prognostic value of c-MET protein expression in gastric cancer patients: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background The heterogeneous nature of c-MET overexpression in gastric cancer (GC) leads to a lack of consensus on its prognostic significance.Objective To evaluate the predictive value of c-MET protein expression in gastric cancer patients.Methods A systematic review of studies from PubMed, Web of Science, Embase, and Cochrane Library up to April 2025. Heterogeneity and robustness were assessed using the Cochrane Q test, I2 statistic, and sensitivity analysis. Publication bias was evaluated with Egger’s and Begg’s tests. The Newcastle-Ottawa Scale (NOS) assessed methodological quality.Results From 2,322 articles, 22 studies were included. High c-MET expression was significantly associated with reduced overall survival (OS) (Hazard Ratio [HR] = 1.22; 95% Confidence Interval [CI]: 1.13, 1.31; I2 = 6.8%; P = 0.371) and disease-free survival (DFS) (pooled HR = 1.39; 95% CI: 1.11, 1.68; I2 = 42.4%; P = 0.139). Definitions of c-MET positivity varied across studies regarding thresholds, staining intensity, and detection methods. Subgroup analysis of OS revealed conflicting conclusions based on study design, cutoff values, and c-MET assays.Conclusion High c-MET expression may independently predict poor GC prognosis. Future efforts should focus on standardized detection methods and high-quality prospective studies to validate its prognostic value.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it