Immunohistochemical detection of cancer-associated fibroblasts in gastrointestinal cancer as a potential prognostic biomarker of survival: meta-analysis
Bibliographic record
Abstract
BACKGROUND: The association between cancer-associated fibroblasts (CAFs) and prognosis of gastrointestinal cancer patients remains controversial. The purpose of the present article is to assess the role of CAFs in gastrointestinal cancer patients by performing a meta-analysis of the clinical trials published in the literature. METHODS: Several studies were conducted to compare survival between high proportion of CAFs and low proportion of CAFs in gastrointestinal cancer patients. Search strategies were performed in PubMed, EMBASE, Medline and the Cochrane Library database. Methodological quality was assessed with the Newcastle-Ottawa Quality Assessment Scale (NOS). RESULTS: Among 3,763 patients enrolled in 18 studies, the pooled hazard ratio (HR) 1.64 (95% CI, 1.43 to 1.87; P<0.001) for overall survival (OS) indicated that a high proportion of CAFs was associated with shorter OS. Among 3,137 patients in 7 studies, the pooled HR 2.56 (95% CI, 1.55 to 4.22, P<0.001) for disease-free survival (DFS) exhibited that a high proportion of CAFs was associated with higher risk of recurrence. The subgroup analyses based on different tumor types showed consistent results. CAFs had no correlation with age, gender, tumor localization, TNM stage, tumor grade, and tumor type. CONCLUSIONS: The meta-analysis indicates that high proportion of CAFs is a valuable predictor of the prognosis in gastrointestinal cancer patients, and it may provide new ideas for targeted therapy in gastrointestinal cancer patients.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.043 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".