Case report: Two cases of leptomeningeal metastases in patients with metastatic urothelial carcinoma treated with enfortumab vedotin
Bibliographic record
Abstract
Background: Leptomeningeal carcinomatosis is an exceptionally rare pattern of metastases in genitourinary cancer, described in less than 0.1% of cases. We report two cases of patients with metastatic urothelial cancer who initially responded to enfortumab vedotin (EV) before developing leptomeningeal metastases. Case presentation: Case 1: A 55 year-old man was diagnosed with metastatic urothelial carcinoma. He was initially treated with cisplatin/gemcitabine chemotherapy, followed by second-line pembrolizumab, with progression on both of these regimens. He was started on EV therapy and had a sustained partial response. After 12 cycles of treatment, he developed neurologic symptoms with imaging showing extensive leptomeningeal metastases. A lumbar puncture was performed with cytology positive for metastatic carcinoma. Case 2: A 63 year-old man was diagnosed with metastatic urothelial carcinoma. He received 6 cycles of platinum/gemcitabine chemotherapy followed by avelumab maintenance, after which he developed radiographic progression. He was started on EV therapy and developed a complete radiographic response. After 13 cycles of treatment, he developed neurologic symptoms and imaging revealed extensive leptomeningeal disease. Cytology confirmed metastatic urothelial carcinoma. Conclusion: This uncommon pattern of spread observed in two patients treated with EV in short succession represents a potentially significant and novel pattern of progression within this population.
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 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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 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".