Ampullary Neuroendocrine Neoplasms: Identification of Prognostic Factors in a Multicentric Series of 119 Cases
Bibliographic record
Abstract
Neuroendocrine neoplasms (NENs) of the major and minor ampulla are rare diseases with clinico-pathologic features distinct from non-ampullary-duodenal NENs. However, they have been often combined and the knowledge on prognostic factors specific to ampullary NENs (Amp-NENs) is limited. The aim of this study was to identify factors associated with metastatic potential and patient prognosis in Amp-NENs. We clinically and histologically investigated an international series of 119 Amp-NENs, comprising 93 ampullary neuroendocrine tumors (Amp-NETs) and 26 neuroendocrine carcinomas (Amp-NECs). Somatostatin-producing tubulo-acinar NET represented the predominant Amp-NET histologic subtype (58 cases, 62%, 12 associated with type 1 neurofibromatosis). Compared to Amp-NETs, Amp-NECs arose in significantly older patients and showed a larger tumor size, a more frequent small vessel invasion, a deeper level of invasion and a higher rate of distant metastasis, and, importantly, a tremendously worse disease-specific patient survival. In Amp-NETs, the WHO grade proved to be a strong predictor of disease-specific survival (hazard ratio: 12.61, p < 0.001 for G2 vs G1), as well as patient age at diagnosis > 60 years, small vessel invasion, pancreatic invasion, and distant metastasis at diagnosis. Although nodal metastatic disease was not associated with survival by itself, patients with > 3 metastatic lymph nodes showed a worse outcome in comparison with the remaining Amp-NET cases with lymphadenectomy. Tumor epicenter in the major ampulla, small vessel invasion, and tumor size > 16 mm were independent predictors of nodal metastases in Amp-NETs. In conclusion, we identified prognostic factors, which may eventually help guide treatment decisions in Amp-NENs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".