A Real-World Retrospective Analysis of the Management of Advanced Urothelial Carcinoma in Canada
Bibliographic record
Abstract
Locally advanced or metastatic urothelial carcinoma (aUC) presents a significant challenge with high mortality rates. Platinum-based chemotherapy remains the established frontline standard of care, and a switch-maintenance strategy with immunotherapy has now emerged as a new standard for aUC patients without disease progression, following initial platinum therapy. Examining the treatment patterns is imperative, given the evolving therapeutic landscape. In this study, we conducted a retrospective medical chart review of 17 Canadian oncologists treating patients with aUC to assess unmet needs in Canadian aUC patient care. Data from 146 patient charts were analyzed, revealing important clinical insights about the management of aUC. A substantial proportion of patients (53%) presented with de novo metastatic disease, which was possibly influenced by pandemic-related care disruptions. Variability was evident in the cisplatin eligibility criteria, with a majority (70%) of oncologists utilizing a 50 mL/min threshold. Most favored four cycles of platinum-based chemotherapy to spare the bone marrow for future therapies and prevent patient fatigue. Notably, some eligible patients were kept under surveillance rather than receiving maintenance therapy, suggesting a potential gap in awareness regarding evidence-based recommendations. Furthermore, managing treatment-related adverse events was found to be one of the biggest challenges in relation to maintenance immunotherapy. In conclusion, our findings provide the first comprehensive overview of aUC treatment patterns in Canada following the approval of maintenance immunotherapy, offering insights into the decision-making process and underscoring the importance of evidence-based guidelines in aUC patient management.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".