Prognostic Ability of Expression of Myofibroblasts in Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
AIM: To systematically review the existing scientific literature in providing a comprehensive, quantitative analysis on the prognostic ability of Cancer Associated Fibroblasts (CAFs) in Oral Squamous Cell Carcinoma (OSCC) a novel meta-analysis. METHODS: Review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and registered in PROSPERO - CRD CRD42023467899. Electronic databases were searched for studies having data on effect of CAFs on overall survival rate and disease prognosis in patients with OSCC, oral epithelial dysplasia (OED) compared to normal healthy controls. Quality assessment of included was evaluated through Newcastle Ottawa scale (NOS) for included studies through its domains. The hazard ratio (HR) and risk ratio (RR) was used as summary statistic measure with random effect model and p value <0.05 as statistically significant. RESULTS: Twenty studies fulfilled the eligibility criteria and were included in qualitative synthesis and eighteen studies for meta -analysis. Included studies had moderate to low risk of bias. It was observed through the pooled estimate that overall survival rate - (HR) =2.30 (1.71 - 3.10) was lesser in group with high CAFs compared to low CAFs while pooled estimate through RR =1.53 (0.73 - 3.19) and RR = 5.72 (2.40 - 13.59) signified that overall survival rate was lower n OSCC patients with high CAF compared to patients with OED and healthy controls. Publication bias through the funnel plot showed asymmetric distribution with presence of systematic heterogeneity indicating presence of publication bias. CONCLUSION: Abundance of CAFs in tumor stroma of OSCC patients is associated with overall poor survival rate and poor disease prognosis. CAFs acts as a good prognostic and therapeutic marker in disease progression and advancements and should be assessed early to reduce patient's mortality and morbidity.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".