Postoperative prognostic factors in patients with T2 gallbladder cancer: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: This study aimed to examine postoperative prognostic factors in patients with T2 gallbladder cancer (GBC) to determine factors linked to survival outcomes. The results can inform clinical decision-making and guide personalized treatment plans. METHODS: The Cochrane Library, PubMed, Web of Science, and Embase databases were retrieved up to March 12, 2025. The included articles were scored via the Newcastle-Ottawa Scale (NOS). The data were analyzed via Stata 15.0. RESULTS: Twenty-one studies (n = 8,095) were included. Factors associated with worse overall survival (OS) included age > 60 years (hazard ratio [HR] = 1.02, 95% confidence interval [CI]: 1.00–1.05) and hepatic-side tumors (HR = 2.89, 95% CI: 2.14–3.90). There was a non-significant trend toward poorer OS with male sex (HR = 1.41, 95% CI: 0.89–2.23). Several associations became significant after sensitivity analyses eliminated sources of heterogeneity: lymph node (LN) metastasis (HR = 2.18, 95% CI: 1.56–3.07), perineural invasion (PNI) (HR = 2.29, 95% CI: 1.74–3.03), simple cholecystectomy (SC) (HR = 1.46, 95% CI: 1.00–2.13), and extended cholecystectomy (EC), the latter of which was protective (HR = 0.67, 95% CI: 0.52–0.87). Additional protective factors included LN dissection (HR = 0.57, 95% CI: 0.38–0.86) and R0 resection (HR = 0.21, 95% CI: 0.05–0.91). For disease-free survival (DFS), LN metastasis (HR = 2.46, 95% CI: 1.50–4.04) and PNI (HR = 2.03, 95% CI: 1.36–3.04) were independent predictors of a poor outcome, which was confirmed again after sensitivity analyses. CONCLUSIONS: For postoperative patients with T2 GBC, factors, including age > 60 years, male gender, hepatic lateral tumor, LN metastasis, PNI, and SC were linked to worse OS. LN metastasis and PNI significantly affected DFS. EC and LN dissection may improve prognosis.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.046 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".