Hepatic resection of noncolorectal nonneuroendocrine metastases
Bibliographic record
Abstract
Because hepatic resection is generally a safe procedure, the indications for resection of noncolorectal nonneuroendocrine (NCNNE) hepatic metastases have broadened. The prognostic features of NCNNE metastases treated surgically were reviewed to define better the value of resection. A retrospective review of patients undergoing liver resection for NCNNE metastases between 1978 and 1998 was undertaken. Thirty-seven patients were identified. Mean age was 56 years, with a median follow-up of 22 months. Primary tumor sites were grouped into gastrointestinal (GI) adenocarcinoma (small bowel, n = 4; pancreas, n = 2; esophagus, n = 1) and other (renal cell, n = 7; sarcoma, n = 7; melanoma, n = 5; adrenal, n = 3; unknown adenocarcinoma, n = 3; thyroid, n = 2; testicular, n = 1; ovarian, n = 1; breast, n = 1). All patients underwent surgery for cure. Metastases were synchronous in 14 patients. There was no surgical mortality. Overall 5-year survival rate was 45%. Five-year survival rates were better for patients with non-GI-origin metastases (60% v 0%; P =.01). Long-term survival was seen only in patients with non-GI-origin metastases. The extent of resection, presence of synchronous metastases, or disease-free interval from time of original disease to presentation with liver metastases were not predictive of outcome. We conclude that patients with NCNNE hepatic metastases can undergo liver resection with an expectation of prolonged survival. However, patients with liver metastases from GI primary tumors other than the colorectum are unlikely to show extended survival.
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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) | 0.002 | 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".