Duodenal neuroendocrine tumors: Short-term outcomes of endoscopic submucosal dissection performed in the Western setting
Bibliographic record
Abstract
Abstract Background and study aims Endoscopic resection (ER) is recommended for the management of duodenal neuroendocrine tumors (D-NETs) confined to the submucosal layer, without lymph node or distant metastasis. While this is accepted practice for lesions < 10 mm, consensus for larger lesions remains unclear. Although endoscopic submucosal dissection (ESD) has been proposed as the preferred ER technique for DNETs ≥10 mm, there are limited data on efficacy and safety, particularly in the Western setting. Patients and methods We performed a retrospective analysis of patients with D-NETs who underwent ESD between 2012 and 2022 in three tertiary referral centers in Australia, France, and Belgium. Results Fourteen patients with 15 D-NETs were evaluated. Median patient age was 64 years (interquartile range [IQR] 58–70 years). All D-NETs were confined to the duodenal bulb. Median D-NET size was 10 mm (IQR 7–12 mm) and specimen size was 15 mm (IQR 15–20 mm). Median procedure time was 60 minutes (IQR 25–90 minutes). The rate of en bloc resection was 100%. Intra-procedural perforation occurred in four patients (26.7%), with all closed endoscopically without long-term sequelae. There were no episodes of clinically significant bleeding. No local recurrence, lymph node or distant metastasis was observed at a median follow-up of 19.9 months (IQR 10.3–49.3 months). Conclusions In experienced hands, ESD for D-NETs can achieve a 100% en bloc resection rate. There were no cases of local recurrence or distant metastatic spread, indicating that ESD may be a viable option for patients with D-NETs 10 to 15 mm that are not surgical candidates.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".