Prognostic and clinicopathological value of Beclin-1 expression in hepatocellular carcinoma: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: The abnormal expression of Beclin-1 has recently been investigated in a variety of tumors. However, previous studies have obtained contradicting results regarding the clinical and prognostic value of Beclin-1 in hepatocellular carcinoma (HCC). We performed a meta-analysis to clarify the prognostic value of Beclin-1 and its correlations with clinical pathological parameters in HCC. METHODS: Relevant studies were systematically retrieved from PubMed, EMBASE, China National Knowledge Infrastructure (CNKI), Wan Fang and Chinese VIP databases. We used the Newcastle-Ottawa scale (NOS) to estimate the quality of the involved studies. RESULTS: Ten eligible studies with 1086 HCC patients were included in this study. Our results showed that decreased Beclin-1 expression in HCC related to histological grade [poor-undifferentiated vs. well-moderate: odds ratio (OR) = 2.34, 95% confidence interval (CI) = 1.65-3.32, P < 0.00001]. The pooled hazard ratio (HR) (HR = 1.43, 95% CI = 1.17-1.75, P = 0.0004) indicated that decreased Beclin-1 expression correlated with poor overall survival (OS). CONCLUSIONS: This meta-analysis indicated that decreased Beclin-1 expression might relate to poor differentiation and unfavorable outcome in HCC.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.019 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".