Significance of the surgical hepatic resection margin in patients with a single hepatocellular carcinoma
Bibliographic record
Abstract
BACKGROUND: The impact of a wide surgical margin on the outcome of patients with hepatocellular carcinoma (HCC) has not been evaluated in relation to the type of liver resection performed, anatomical or non-anatomical. The aim of this study was to evaluate the impact of surgical margin status on outcomes in patients undergoing anatomical or non-anatomical resection for solitary HCC. METHODS: Data from patients with solitary HCC who had undergone non-anatomical partial resection (Hr0 group) or anatomical resection of one Couinaud segment (HrS group) between 2000 and 2007 were extracted from a nationwide survey database in Japan. Overall and recurrence-free survival associated with the surgical margin status and width were evaluated in the two groups. RESULTS: A total of 4457 patients were included in the Hr0 group and 3507 in the HrS group. A microscopically positive surgical margin was associated with poor overall survival in both groups. A negative but 0-mm surgical margin was associated with poorer overall and recurrence-free survival than a wider margin only in the Hr0 group. In the HrS group, the width of the surgical margin was not associated with patient outcome. CONCLUSION: Anatomical resection with a negative 0-mm surgical margin may be acceptable. Non-anatomical resection with a negative 0-mm margin was associated with a less favourable survival outcome.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".