Prognostic Significance of Tumor-Stroma Ratio in Hepatocellular and Gallbladder Carcinomas: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The tumor microenvironment plays a crucial role in cancer progression, with the tumor-stroma ratio (TSR) emerging as a prognostic marker in solid tumors. A high TSR, indicating a greater proportion of tumor cells relative to stromal tissue, has been associated with improved survival. However, its prognostic value in hepatocellular carcinoma (HCC) and gallbladder carcinoma (GBC) remains unclear. This meta-analysis aims to assess the prognostic significance of TSR in these cancers. Materials and methods: A systematic search of PubMed, Scopus, and Web of Science was conducted following PRISMA guidelines. Eligible cohort studies assessing TSR in HCC and GBC were included. Hazard ratios (HRs) for overall survival were pooled using a random-effects model. Heterogeneity was assessed using the I² statistic. The risk of bias was evaluated using the Newcastle-Ottawa Scale. Results: Four retrospective cohort studies with 542 patients were included. A high TSR was significantly associated with improved survival in HCC (HR: 2.566, 95% CI: 1.028–4.104) but showed a weaker, non-significant association in GBC (HR: 1.568, 95% CI: 0.327–2.809). No publication bias was detected (Egger’s test, p=0.552). Conclusion: This meta-analysis highlights TSR as a potential prognostic marker in HCC, where a high TSR is associated with improved survival. In GBC, the prognostic significance of TSR remains uncertain, possibly due to tumor heterogeneity and advanced-stage diagnoses. Given its prognostic value, TSR could be integrated into routine histopathological assessments, particularly in HCC, to enhance risk stratification and guide clinical decision-making.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".