Living vs. deceased donor liver transplantation for hepatocellular carcinoma: a systematic review and meta‐analysis
Bibliographic record
Abstract
Experimental studies suggest that the regenerating liver provides a "fertile field" for the growth of hepatocellular carcinoma (HCC). However, clinical studies report conflicting results comparing living donor liver transplantation (LDLT) and deceased donor liver transplantation (DDLT) for HCC. Thus, disease-free survival (DFS) and overall survival (OS) were compared after LDLT and DDLT for HCC in a systematic review and meta-analysis. Twelve studies satisfied eligibility criteria for DFS, including 633 LDLT and 1232 DDLT. Twelve studies satisfied eligibility criteria for OS, including 637 LDLT and 1050 DDLT. Altogether, there were 16 unique studies; 1, 2, and 13 of these were rated as high, medium, and low quality, respectively. Studies were heterogeneous, non-randomized, and mostly retrospective. The combined hazard ratio was 1.59 (95% confidence interval [CI]: 1.02-2.49; I(2) = 50.07%) for DFS after LDLT vs. DDLT for HCC, and 0.97 (95% CI: 0.73-1.27; I(2) = 5.68%) for OS. This analysis provides evidence of lower DFS after LDLT compared with DDLT for HCC. Improved study design and reporting is required in future research to ascribe the observed difference in DFS to study bias or biological risk specifically associated with LDLT.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.004 | 0.007 |
| 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) | 0.003 | 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".