Is the Real Prevalence of Pancreatic Neuroendocrine Tumors Underestimated? A Retrospective Study on a Large Series of Pancreatic Specimens
Bibliographic record
Abstract
BACKGROUND/AIMS: The annual incidence of pancreatic neuroendocrine tumors (PanNET) has been estimated to be around 0.8/100,000 inhabitants. The aim of this study was to determine the frequency of incidental histological diagnosis of PanNET in pancreatic specimen evaluation for a purpose other other than PanNET diagnosis. METHODS: One thousand seventy-four histopathological examinations of pancreatic specimens performed in 3 centers in Italy were retrospectively reviewed. All cases with a main pathological diagnosis of PanNET were excluded. RESULTS: An incidental associated diagnosis of PanNET was made in 41 specimens (4%). Among those 41 cases, 29 (71%) had a largest diameter <5 mm (microadenoma), whereas the other 12 (29%) had a maximum size ≥5 mm (median diameter of the whole series = 3 mm, range 1-15). The association with a main diagnosis of intraductal papillary mucinous neoplasms (IPMN) was significantly higher for patients who had an incidental PanNET (p = 0.048). There was no association between incidental diagnosis of PanNET and age, gender, BMI, smoking habit, diabetes, and type of operation. CONCLUSIONS: The frequency of incidental histological diagnosis of PanNET is considerably high, suggesting that their real prevalence is probably underestimated. The present study suggests a possible correlation between the incidental occurrence of PanNET and IPMN.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".