The effect of tumor location on overall survival for pT2-4 bladder and upper tract urothelial carcinoma following radical surgery
Bibliographic record
Abstract
INTRODUCTION: Historically, staging and treatment for upper tract urothelial carcinoma were extrapolated from bladder urothelial carcinoma literature. However, embryological, genetic, and anatomical differences exist between them. We sought to explore the relationship between location of urothelial cancer and overall survival (OS). METHODS: Data was culled from the National Cancer Database from 2004-2015. Patients with pT2-pT4 treated with definitive surgery were included; those with metastatic disease or who received neoadjuvant or adjuvant treatment were excluded. Patients were stratified by tumor location and pathological stage. The primary outcome was OS. Secondary outcomes were predictors of mortality in each pT stage stratum. RESULTS: A total of 11 330 patients with bladder, 954 patients with ureteral, and 1943 patients with renal pelvis urothelial carcinoma were analyzed. Mean followup was 43.3, 39.4, and 41.4 months for bladder, ureteral, and renal pelvis, respectively. On univariable analysis, ureteral pT2 was associated with worse OS compared to both bladder (61.3 vs. 80.4 months, p=0.007) and renal pelvis (61.3 vs. 80.5 months, p=0.014). Renal pelvis pT3 was associated with improved OS compared to both bladder (42.5 vs. 28.6 months, p=0.003) and ureteral (42.5 vs. 25.7 months, p<0.001). Renal pelvis pT4 had decreased survival compared to bladder (11.4 vs. 17.7 months, p<0.001). On multivariable Cox regression, only renal pelvis pT3 was associated with a 20% decreased risk of mortality compared to bladder pT3 (hazard ratio 0.80, 95% confidence interval 0.72-0.88, p<0.001). CONCLUSIONS: Renal pelvis pT3 is associated with lower mortality. Mutational and embryological differences may play a role in this disparity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".