Survival of Metastatic Urothelial Carcinoma of Urinary Bladder According to Number and Location of Visceral Metastases
Bibliographic record
Abstract
OBJECTIVE: To test the association between number as well as locations of organ-specific metastatic sites and overall survival (OS) in systhemic-therapy exposed metastatic urothelial carcinoma of urinary bladder (mUCUB) patients. METHODS: Within Surveillance, Epidemiology and End Results database (2010-2020), all systhemic therapy-exposed mUCUB patients were identified. Kaplan-Meier and multivariable Cox regression (CRM) models first addressed OS in patients according to number of metastatic organ-locations: solitary versus 2 versus 3 or more. Subsequently, separate analyses stratified according to location type were completed in patients with solitary metastatic organ-location as well as in patients with 2 metastatic organ-locations. RESULTS: Of 1,310 mUCUB, 1,069 (82%) harbored solitary metastatic organ-location versus 193 (15%) harbored 2 separate metastatic organ-locations versus 48 (3%) harbored 3 or more metastatic organ-locations. Median OS decreased with increasing number of metastatic organ-locations (solitary vs. 2 vs. 3 or more, P < .0001). In multivariable CRM, relative to solitary metastatic organ-location, 2 (HR: 1.57, 95 Confidence interval [CI], 1.33-1.85) as well as 3 or more (HR: 1.69, 95% CI, 1.23-2.31) metastatic organ-locations independently predicted higher overall mortality (OM) (P = .001). In patients with solitary metastatic organ-location, brain metastases independently predicted higher OM (HR 1.67; 95% CI, 1.05-2.67; P = .03) than other locations. In patients with 2 metastatic organ-locations, no differences in OM were recorded according to organ type location. CONCLUSION: In systemic therapy exposed mUCUB, number of metastatic organ-locations (solitary vs. 2 vs. 3 or more), independently predicted increasingly worse prognosis. In patients with solitary metastatic organ-location, brain purported worse prognosis than others.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".