Harm and Benefits of Salvage Transplantation for Hepatocellular Carcinoma: An Updated Meta-analysis
Bibliographic record
Abstract
OBJECTIVE: The aim of this work was to compare salvage liver transplantation (SLT) and primary liver transplantation (PLT) in terms of the harm and benefits. METHODS: The authors searched Pubmed, Embase, and the Cochrane Library from their dates of establishment to December 2015. Based on selection and exclusion criteria, 2 researchers screened the literature independently. The meta-analysis was performed with the use of the Review Manager software. Meta-analysis of the pooled standard mean difference (SMD) and odds ratio (OR) with 95% confidence interval (CI) were calculated based on either a fixed-effects or a random-effects model. In addition, risk of bias was assessed with the use of the Newcastle-Ottawa scale. RESULTS: Sixteen studies were selected, involving almost 8,707 patients. According to the pooled estimates, compared with PLT, SLT was associated with a longer operative time (SMD, 0.28; 95% CI, 0.11-0.46;), higher intraoperative blood loss (SMD, 0.41; 95% CI, 0.08-0.75;), more postoperative bleeding (OR, 1.95; 95% CI, 1.10-3.45), an increased risk of recurrence (OR, 2.08; 95% CI, 1.24-3.50), and poorer 3-year (OR, 0.86; 95% CI, 0.76-0.98) and 5-year (OR, 0.86; 95% CI, 0.76-0.98) overall survival rates. However, no difference was detected between case and control groups in either rates of postoperative complications or such aspects as perioperative mortality, length of intensive care unit stay, length of hospital stay, and 1-year overall survival rate. CONCLUSIONS: The 3-year and 5-year overall survival rates were inferior in SLT, which shows that PLT is a better treatment strategy for transplantable hepatocellular carcinoma (HCC). However, considering the severe organ limitation and the feasibility and safety of SLT, it provides a better option for patients with HCC recurrence after curative resection.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.049 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".