Demographics, Clinical Characteristics and Survival Outcomes of Primary Urinary Tract Malignant Melanoma Patients: A Population-Based Analysis
Bibliographic record
Abstract
All primary urinary tract malignant melanoma (ureter vs. bladder vs. urethra) patients were identified from within the Surveillance, Epidemiology, and End Results (SEER) database 2000–2020. Kaplan-Maier plots depicted the overall survival (OS) rates. Univariable and multivariable Cox regression (MCR) models were fitted to test the differences in overall mortality (OM). In the overall cohort (n = 74), the median OS was 22 months. No statistically significant or clinically meaningful differences were recorded according to sex (female vs. male; p = 0.9) and treatment of the primary (endoscopic vs. surgical; p = 0.6). Conversely, clinically meaningful but not statistically significant (p ≥ 0.05) differences were recorded according to the patient’s age at diagnosis (≤80 vs. ≥80 years old; p = 0.2), marital status (married 26 vs. unmarried 16 months; p = 0.2), and SEER stage (localized 31 vs. regional 14 months; p = 0.4), and the type of systemic therapy (exposed 31 vs. not exposed 20 months; p = 0.06). Finally, in univariable and MCR analyses, after adjustment for the SEER stage and type of systemic therapy, tumor origin within the bladder was associated with a three-fold higher OM (Hazard ratio: 3.00; p = 0.004), compared to tumor origin within the urethra. In conclusion, primary urinary tract malignant melanoma patients have poor survival. Specifically, tumor origin within the bladder independently predicted a higher OM, even after adjustment for the SEER stage and systemic therapy status.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".