Gender-related Outcome in Bladder Cancer Patients undergoing Radical Cystectomy
Bibliographic record
Abstract
Background: The impact of gender on oncological outcome after radical cystectomy (RC) is not fully understood yet.The aim of the study was to evaluate gender-related differences in histopathological parameters and prognosis of patients with bladder cancer undergoing RC.Methods: A retrospective analysis of a 10-year single-center cystectomy database was performed.Kaplan-Meier survival and Cox-regression analyses with sex-specific interactions were performed to determine the impact of gender on recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS), in addition to established clinicopathological factors.Results: 259 patients (212 [81.8%] men and 47 [18.2%] women) were enrolled.Although women had a greater propensity for extravesical (≥pT3) disease (53.2% vs. 33.9%,p=0.03) and heterotopic urinary diversion (72.3% vs. 49.5%,p=0.006), gender did not independently predict RFS, CSS or OS on multivariate analysis.Extravesical tumor disease was the sole independent predictor concerning RFS (hazard ratio [HR]=4.70;p<0.001),CCS (HR=2.77;p=0.013), and OS (HR=1.93;p=0.041).Orthotopic urinary diversion (HR=0.36;p=0.002) had an independent effect only on RFS.Rates of 5-year RFS (73.7% vs. 48.3%;p=0.001),CSS (72.5% vs. 44.9%;p<0.001) and OS (62.6% vs. 37.8%; p<0.001) were higher in orthotopic versus heterotopic diversions.Conclusion: In our series, women presented with more advanced tumors and higher rates of heterotopic urinary diversions, but their survival outcome was not significantly inferior to that of men.Extravesical disease was independently related to poorer survival after RC.
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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 | 0.002 |
| 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".