Simultaneous, Delayed and Liver-First Hepatic Resections for Synchronous Colorectal Liver Metastases: A Systematic Review and Network Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Systematic reviews and meta-analyses that compare simultaneous, delayed and liver-first approach for synchronous colorectal liver metastases have found no significant differences. The aim of this study was to determine the best treatment strategy on the basis of effect sizes and the probabilities of treatment ranking by using a network meta-analysis. Moreover, first-time pairwise and network meta-analyses were used to estimate the existing evidence, and their results were compared to detect any discrepancies between them. METHODS: Systematic review, pairwise meta-analysis and network meta-analysis were performed. The primary and secondary outcomes were 5-year overall survival and postoperative major morbidity, respectively. RESULTS: No significant differences in long-term survival and major morbidity were found amongst the three approaches. The hazard ratios (95% confidence interval) for 5-year overall survival for the simultaneous, delayed and liver-first approaches were 0.93 (0.69 - 1.24, P = 0.613), 0.97 (0.87 - 1.07, P = 0.596) and 0.90 (0.67 - 1.22, P = 0.499), respectively. Moreover, the liver-first approach with a surface under the cumulative ranking area score of 89% was ranked as the potentially best treatment option based on probabilities of treatment ranking. CONCLUSIONS: On the basis of the relative ranking of treatments, the liver-first approach ranked first, followed by the delayed and simultaneous approaches. Therefore, a three-arm randomized controlled trial that compares the liver-first, simultaneous and delayed approaches needs to shed further light as to which is the best treatment option.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| grok | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| opus | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | medium |
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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.040 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".