Presentation, treatment and outcome in patients with ampullary tumours
Bibliographic record
Abstract
BACKGROUND: Ampullary tumours are relatively rare, and few large single-centre reports provide information on their treatment and outcome. The aim of this study was to analyse outcome and determine predictors of survival for patients with ampullary tumours treated in a specialist centre. METHODS: Over an 11-year period, 561 patients were treated for periampullary tumours, 88 of whom had a histologically proven ampullary neoplasm. Prospectively gathered data were analysed to assess predictors of survival. RESULTS: The overall resection rate was 92 per cent; there were no postoperative deaths. Median survival was 45.8 months for patients with resectable tumours and 8.0 months for those with irresectable disease (P < 0.001). On univariate analysis, age less than 70 years (P = 0.015) and a bilirubin level of 75 micromol/l or less (P = 0.012) favoured long-term survival. Among 70 patients who underwent cancer resection, factors associated with significantly worse long-term survival on univariate analysis included poorly differentiated tumour (P < 0.001), positive nodes (P < 0.001), perineural invasion (P = 0.001) and invasion of the pancreas (P = 0.018). Multivariate analysis identified positive nodes and bilirubin concentration as independent predictors of survival. CONCLUSION: An aggressive surgical approach to ampullary tumours is justified by the low proportion of benign lesions, the absence of postoperative mortality and improved long-term 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".