Bladder Preservation in Muscle-Invasive Bladder Cancer: A Population-Based Analysis from British Columbia
Bibliographic record
Abstract
Bladder cancer is the 5th most common cancer in Canada and a quarter of diagnosed patients have muscle-invasive bladder cancer (MIBC). Standard treatment options, systemic therapy and radical cystectomy (RC) are associated with high rates of adverse outcomes. Recently, trimodal treatment (TMT), a bladder preservation strategy defined as maximal transurethral resection of bladder tumor (TURBT) and chemoradiation, has been considered an alternative per guidelines for select patients who prefer bladder preservation or those with comorbidities. Nevertheless, the uptake of bladder preservation strategies in Canada remains low. We conducted a retrospective evaluation in British Columbia (BC) to assess the real-world outcomes of bladder-sparing radiotherapy. Cohort treated with combined chemoradiotherapy (concurrent and/or adjuvant, neoadjuvant chemotherapy) showed numerical improvements across all evaluated endpoints, including disease-specific survival and progression-free survival, compared with radiation therapy alone, which is generally considered an inferior strategy. However, these differences did not reach statistical significance, contrasting with the literature. Despite the limitations posed by the small sample size and the study's retrospective design, the findings highlight the pivotal role of appropriate patient selection in achieving meaningful therapeutic outcomes. Future studies integrating biomarker-driven strategies are needed to enhance outcomes through individualized treatment selection, particularly for older patients with multiple comorbidities.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".