Liver Histology and Surgical Outcomes After Preoperative Chemotherapy With Fluorouracil Plus Oxaliplatin in Colorectal Cancer Liver Metastases
Bibliographic record
Abstract
PURPOSE: Preoperative chemotherapy for colorectal liver metastases (CLM) can produce histologic changes in the nontumor-bearing liver (NTBL) that may impact on surgical outcomes. PATIENTS AND METHODS: From a cohort of 303 patients treated for CLM with liver resection, 92 patients (75 received preoperative chemotherapy: group C+; and 17 were chemotherapy naïve: group C-) were randomly selected for detailed pathologic analysis. Preoperative chemotherapy consisted of fluorouracil (FU)/leucovorin alone (23 patients, the majority chronomodulated) or in combination with oxaliplatin (52 patients, all chronomodulated). To determine associations between study factors, clinical and operative variables were compared with pathology data and surgical outcomes. RESULTS: Although clinical and operative factors were similarly distributed, C+ patients, compared with C- patients, were more likely to receive intraoperative RBC transfusions (mean units: 1.9 v 0.5, respectively; P = .03) and to have vascular abnormalities in the NTBL (52% v 18%, respectively; P = .01). Presence of the most severe forms of vascular alterations was closely associated with RBC transfusion requirements (P = .04). In contrast, moderate to severe steatosis was similarly distributed (C- group, 12%; C+ group, 13%). Although perioperative mortality and morbidity rates were similar in all groups, more than 12 courses of chemotherapy, compared with < or = 12 courses, predisposed patients to reoperation (11% v 0%, respectively; P = .04) and to longer hospitalization (15 v 11 days, respectively; P = .02). CONCLUSION: The main hepatic lesion induced by preoperative FU/oxaliplatin chemotherapy in patients with CLM is vascular and not steatosis. Detailed pathologic analysis determined that the most severe vascular lesions are associated with increased intraoperative transfusions. The risk for other postoperative complications is related to the duration of preoperative chemotherapy administration.
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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".