Survival After Partial Cystectomy Versus Radical Cystectomy for Non-Urothelial Carcinoma of the Bladder: A Population-Based Study
Bibliographic record
Abstract
Background: The aim of this study was to compare cancer-specific survival (CSS) and overall survival (OS) after partial cystectomy (PC) versus radical cystectomy (RC) in patients with stage T2N0M0 non-urothelial carcinoma of the bladder (NUCB). Methods: Data on patients with stage T2N0M0 NUCB treated with PC or RC were retrospectively retrieved from the Surveillance, Epidemiology, and End Results (SEER) database from 2007 to 2015. Propensity score matching (PSM) was used to create matched cohorts, which were used to calculate OS and CSS. Results: Among 999 histologically confirmed NUCB patients (752 in PC group and 247 in RC group), significant differences were found in age, marital status, tumor-related features, and treatment modalities. After 1:1 PSM, 169 pairs were obtained. In the matched cohort, the RC group had significantly higher 1-year, 3-year, and 5-year OS and CSS rates than the PC group (OS: P = 0.002; CSS: P = 0.004). Cox regression analysis showed that older age, unmarried status, and PC were independent risk factors for poor prognosis, while RC was associated with improved survival (OS: hazard ratio (HR) = 0.34, 95% confidence interval (CI): 0.26 - 0.44, P < 0.001; CSS: HR = 0.47, 95% CI: 0.31 - 0.72, P < 0.001). T2b-stage patients had lower cancer-specific mortality than T2a-stage patients (P = 0.01). Subgroup analysis indicated that RC generally led to better survival, except in the neuroendocrine carcinoma subgroup for OS (P = 0.085) and the other carcinoma subgroup for CSS (P = 0.132). Conclusions: This study reveals that RC is associated with superior CSS and OS compared to PC in patients with NUCB. Patient-related factors (age and marital status) and histological subtype significantly influence prognosis, highlighting the need for personalized treatment strategies.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".