Role of neoadjuvant chemotherapy in resectable synchronous colorectal liver metastasis; An international multi‐center data analysis using LiverMetSurvey
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The use of neo-adjuvant chemotherapy in resectable synchronous liver metastasis is ill defined. The aim of this study was to evaluate neo-adjuvant chemotherapy on outcomes following liver resection for synchronous CLM. METHODS: An analysis of a multi-centric cohort from the LiverMetSurvey International Registry, who had undergone curative resections for synchronous CLM was undertaken. Patients who received neo-adjuvant chemotherapy prior to liver surgery (group NAS; n = 693) were compared with those treated by surgery alone (group SG; n = 608). Baseline clinicopathological variables were compared. Predictors of overall (OS) and disease free survival (DFS) were subsequently identified. RESULTS: Clinicopathological comparison of the groups revealed a greater proportion of solitary metastasis in the SG compared to the NAS group (58.8% versus 38.4%; P < 0.001) therefore a separate analysis of solitary versus multi-centric analysis was performed. N-stage (> N1), number of metastasis (> 3), serum CEA (> 5 ng/ml) and no adjuvant chemotherapy independently predicted poorer OS, while N-stage (> N1), serum CEA (> 5 ng/ml) and no adjuvant chemotherapy independently predicted poorer DFS. Neo-adjuvant chemotherapy did not independently affect outcome. CONCLUSION: We present an analysis of a large multi-center series of the role of neo-adjuvant chemotherapy in resectable CLM and demonstrate no survival advantage in this setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".