Liver resection in patients with eight or more colorectal liver metastases
Bibliographic record
Abstract
BACKGROUND: Patients with large numbers of colorectal liver metastases (CRLMs) are potential candidates for resection, but the benefit from surgery is unclear. METHODS: Patients undergoing resection for CRLMs between 1998 and 2012 in two high-volume liver surgery centres were categorized according to the number of CRLMs: between one and seven (group 1) and eight or more (group 2). Overall (OS) and recurrence-free (RFS) survival were compared between the groups. Multivariable analysis was performed to identify adverse prognostic factors. RESULTS: A total of 849 patients were analysed: 743 in group 1 and 106 in group 2. The perioperative mortality rate (90 days) was 0.4 per cent (all group 1). Median follow-up was 37.4 months. Group 1 had higher 5-year OS (44.2 versus 20.1 per cent; P < 0.001) and RFS (28.7 versus 13.6 per cent; P < 0.001) rates. OS and RFS in group 2 were similar for patients with eight to ten, 11-15 or more than 15 metastases (48, 40 and 18 patients respectively). In group 2, multivariable analysis identified three preoperative adverse prognostic factors: extrahepatic disease (P = 0.010), no response to chemotherapy (P = 0.023) and primary rectal cancer (P = 0.039). Patients with two or more risk factors had very poor outcomes (median OS and RFS 16.9 and 2.5 months; 5-year OS zero); patients in group 2 with no risk factors had similar survival to those in group 1 (5-year OS rate 44 versus 44.2 per cent). CONCLUSION: Liver resection is safe in selected patients with eight or more metastases, and offers reasonable 5-year survival independent of the number of metastases. However, eight or more metastases combined with at least two adverse prognostic factors is associated with very poor survival, and surgery may not be beneficial.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".