No Outcome Differences after Cystectomy between Patients with De Novo Muscle-Invasive Bladder Cancer Compared to Progressors: A Retrospective Population-Based Study
Bibliographic record
Abstract
PURPOSE: Whether patients who progress to muscle-invasive bladder cancer have worse outcomes compared to those that present de novo is important for clinical decision making. The objective of this study was to determine if there is a difference in survival after radical cystectomy for de novo cases compared to progressors. MATERIALS AND METHODS: This retrospective, population-based study reports on all patients who underwent radical cystectomy in Ontario utilizing records linked to the Ontario Cancer Registry. The primary objective was to determine if survival was associated with presentation. Secondary objectives included describing processes-of-care between the cohorts and investigate differential responses to chemotherapy. Cox proportional-hazards regression models were used to adjust for known confounders. RESULTS: Between 2009 and 2013, 1,573 patients underwent radical cystectomy with 893 in the de novo cohort while 680 were identified as progressors. After adjusting by stage prior to cystectomy, several processes of care indicators and early outcomes were comparable between the cohorts. In adjusted analysis there were no differences in outcomes; compared to the reference de novo presentation, the hazards ratios (95% confidence interval) for progressors were 0.98 (0.85-1.14) for cancer-specific survival and 1.0 (0.88-1.10) for overall survival. There was no effect modification of chemotherapy based on presentation for cancer-specific survival. Lack of information about those progressors that never received cystectomy is a major limitation. CONCLUSIONS: When controlled for stage, no clinically significant differences in survival outcomes were identified between bladder cancer patients undergoing cystectomy presenting with de novo muscle-invasive bladder cancer compared to progressors in routine clinical practice.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".