Colorectal cancer hepatic metastases resection margins outcomes: a single-centre retrospective cohort study
Bibliographic record
Abstract
Background: Surgical resection is the most efficient treatment for isolated colorectal cancer hepatic metastases. Among the known prognostic factors of this procedure, the impact of the resection margin width is still a controversial matter in the literature. Methods: A retrospective cohort study was performed including 170 patients who underwent surgical resection of colorectal cancer liver metastases (CRLMs) between 2006 and 2016 in our hepatobiliary unit. Resection margin width was determined histologically by measuring the distance from the tumour in millimetres or centimetres. Patients’ clinical characteristics were also collected. Patients were then stratified in two tumour margin groups: below 5 mm (group A) and equal to or above 5 mm (group B). Overall survival (OS) and disease-free survival (DFS) were the primary outcomes. Results: Kaplan–Meier curves showed significantly better outcomes for cases having resection margins above 5 mm for both DFS with 1508.7 days (range 1151.2–1866.2) in group A, compared to 2463.9 days (range 2021.3–2906.5) in group B (P=0.049), and OS with 1557.8 days (range 1276.3–1839.3) for group A and 2303.8 days (range 1921.2–-2686.4) for group B (P=0.020). This survival benefit was not significant for patients presenting with stage IV CRC at diagnosis or cases where extended (7+ segments) resections were performed. Conclusion: Five-millimetre margins provide a significant survival advantage and should be aimed for in the treatment of CRLMs. Further research on the cause for this finding, including tumour biology’s impact on survival, is required.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".