“Not-So-Indolent” neuroendocrine neoplasms: two case reports of gastrointestinal small cell neuroendocrine carcinomas
Bibliographic record
Abstract
Background: Small cell neuroendocrine carcinomas (SCNECs) of the gastrointestinal (GI) tract are exceedingly rare and aggressive malignancies. Unlike pulmonary SCNECs, which are well-characterized, extrapulmonary GI-SCNECs lack established diagnostic pathways and treatment algorithms due to their rarity and histopathological overlap with other poorly differentiated tumors. Literature on their clinical course remains limited to isolated reports, with scarce data on site-specific presentations. These two cases contribute to the existing literature by illustrating distinct primary GI sites (gastric and rectal), underscoring the challenges in early diagnosis and the aggressive clinical progression despite intervention. Case Description: The first patient, an 80-year-old man, presented with progressive dysphagia and dyspnea. Imaging revealed mediastinal lymphadenopathy and gastric wall thickening. Endoscopic biopsies confirmed gastric SCNEC with widespread metastases. Despite initiation of palliative care, his condition deteriorated rapidly, and he died one month after diagnosis. The second patient, a 69-year-old man, presented with significant weight loss and lower abdominal pain. Colonoscopy identified a circumferential rectal mass, and biopsies confirmed SCNEC. Staging demonstrated hepatic and nodal metastases. He received platinum-based chemotherapy and pelvic radiotherapy, achieving only transient stabilization. Following treatment cessation, his disease progressed, and despite resuming chemotherapy, he died 11 months after diagnosis. Conclusions: These cases emphasize the necessity for heightened clinical suspicion of SCNEC in rapidly progressive GI malignancies, even in atypical presentations. Early recognition and multidisciplinary management are crucial, although current therapeutic options offer limited durability. By delineating site-specific clinical courses, this report contributes to the limited body of evidence on GI-SCNECs and underscores the urgent need for standardized diagnostic criteria and treatment protocols to improve outcomes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".