Composite gangliocytoma/neuroma and neuroendocrine tumour: a contemporary analysis of 71 cases shows risk factors for metastasis
Bibliographic record
Abstract
AIMS: To describe the clinicopathological features of composite gangliocytoma/neuroma and neuroendocrine tumour (CoGNET) and possible risk factors for nodal metastasis. METHODS AND RESULTS: We compiled a cohort of 71 cases from 19 institutions. Mean patient age was 58 years. Thirty-eight (54%) patients were male. Most patients (65%) had symptoms, including abdominal pain (20%) and gastrointestinal bleeding (19%). Most cases (70%) were described as a subepithelial mass/nodule, and nearly half (45%) were located in the 2nd portion of the duodenum. Mean tumour size was 2.2 cm, and most (87%) were well-circumscribed. Nearly all cases (96%) demonstrated all three histologic components, with the epithelioid component being the most predominant overall (mean 59%). All cases involved the submucosa, with 7 (10%) additionally involving the muscularis propria. Solid areas of ganglion-like cells were identified in 16/69 (23%) cases, glandular structure formation in 15/70 (21%), lymphovascular invasion (LVI) in 6/70 (9%) cases, and perineural invasion and necrosis in one case each. Nodal metastasis was identified at diagnosis in 8 (11%) cases; increased age, increased size, LVI and muscularis propria involvement were all significantly associated with nodal disease (P < 0.05). Follow-up data were available for 68 patients (mean 47 months); nearly all were alive without disease, though one patient developed liver metastasis after 8 months and died of the disease after 63 months. CONCLUSIONS: This largest series of CoGNET to date demonstrates that approximately 10% of cases develop nodal metastases. Large tumour size, muscularis propria involvement, advanced patient age and LVI appear to be risk factors for nodal metastasis.
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 | 0.000 |
| 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".