Benchmarking Oncologic Outcomes of Liver Resection for Colorectal Metastases
Bibliographic record
Abstract
OBJECTIVE: The present study aims to establish reference standard values for liver resection outcomes in patients with colorectal liver metastases (CRLM) across different tumor burdens. BACKGROUND: Liver surgery has long been the only potentially curative treatment for CRLM, but now options are rising, such as thermal ablation for patients with small oligonodular lesions and liver transplantation for those with high tumor burden. Elucidating surgical outcomes of resective surgery is crucial to defining its role. METHODS: All patients included in the LiverMetSurvey registry between 2000 and 2022 were considered. Only patients undergoing complete resection in high-volume centers without extrahepatic disease and with follow-up >1 year were included. The analyzed outcomes were: 90-day mortality, and 1, 3, and 5-year overall survival (OS) and recurrence-free survival (RFS). Patients were divided into subgroups based on tumor burden, and the analysis was restricted to "benchmark" patients, selected on preoperative chemotherapy administration and response. RESULTS: Overall, 12154 patients treated across 43 centers were enrolled. Ninety-day mortality rate was <5% for most groups. Benchmark value for one-year OS rate exceeded 85% across all subgroups, except for patients with 10 or more CRLM (≥78%). Benchmark values for 5-year OS rates were: ≥45% for solitary synchronous metastases and ≥58% for solitary metachronous ones (if ≤30 mm, ≥54% and ≥67%, respectively); ≥48% for 2 to 3 metastases; ≥28% for more than 3 metastases; and ≥29% for initially unresectable disease. Benchmark values for 5-year RFS rates were: ≥22% for solitary synchronous metastases; ≥36% for solitary metachronous ones; ≥21% for 2 to 3 metastases; ≥15% for 4 to 9 metastases; ≥4% for 10 or more metastases; and ≥10% for initially unresectable disease. CONCLUSIONS: Liver resection has an excellent oncologic effectiveness, even in patients with severe tumor burden. The reference standard values for key oncologic outcomes should serve as benchmarks for evaluating and testing alternative treatments.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".