Primary Large Cell Neuroendocrine Carcinoma of the Urinary Bladder
Bibliographic record
Abstract
Reports of primary large cell neuroendocrine carcinomas of the urinary bladder are few; we identified only 2 cases in the literature. Both of these cases involved male patients with rapid progression of disease culminating in death with widespread metastases. We report a case of primary large cell neuroendocrine carcinoma of the bladder, with an admixed minor element of adenocarcinoma, in an 82-year-old man. This solitary lesion arose in a bladder diverticulum lateral to the left ureteric orifice. Two attempts at transurethral resection were unsuccessful at achieving local control. The patient underwent a partial cystectomy with left-sided pelvic lymphadenectomy following preoperative staging investigations that found no metastatic disease. Pathologically, the tumor invaded into the deep aspect of the muscularis propria, without extension into perivesical fat. The lateral resection margin was microscopically positive for tumor, but no malignancy was found in the pelvic lymph nodes. The adenocarcinoma comprised less than 5% of total tumor volume, and areas of transition between the neuroendocrine and adenocarcinoma components were apparent. The patient developed a local recurrence 8 months postoperatively, which was managed by a combination of transurethral resection and radiation therapy. Currently, the patient has no evidence of local or metastatic disease 2 years after initial diagnosis.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".