Risk factors for survival following recurrence after first liver resection for colorectal cancer liver metastases
Bibliographic record
Abstract
BACKGROUND: Management of recurrence following liver resection for colorectal cancer metastases is a topic of debate. We determined risk factors for survival following recurrence after liver resection. METHODS: Long-term follow-up of patients in the PETCAM trial who had recurrence following liver resection. Risk groups were created according to their survival risk. Differences in overall survival (OS) between groups were estimated. Disease-free survival (DFS), patterns of disease recurrence and management were determined. Cox proportional hazard models, Kaplan-Meier method, and the log-rank test were used. RESULTS: Among 368 patients who underwent liver resection, 264 (72%) experienced disease recurrence (51% lung and 41% liver). Following liver resection, DFS: 17 months (95% CI, 14-19); OS: 57 months (95% CI, 46-70). In those who recurred, 120 (45%) received chemotherapy only, and 112 (42%) underwent second surgical resection. Among patients who experienced recurrence (n = 264), the high-risk group (more than one site of recurrence or disease-free duration < 5 months and node-positive disease) had median OS: 19 months (95% CI, 15-23) vs 36 months (95% CI, 30-48) for patients in the low-risk group (HR = 2.9, 95% CI, 2.2-3.9). CONCLUSION: Recurrence following liver resection is common. Following recurrence after liver resection, patients should be carefully selected for surgical re-resection based on risk factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".