Clinical Benefit of Pembrolizumab in Advanced Urothelial Cancer Patients in Real-Life Setting: An Efficacy and Safety Monocentric Study
Bibliographic record
Abstract
BACKGROUND: Pembrolizumab is approved for patients with metastatic urothelial carcinoma (UC) who progressed under platinum therapy. The aim of this study was to assess the efficacy and safety of pembrolizumab in a cohort of real-life UC patients. METHODS: This retrospective, observational study included advanced UC patients treated with pembrolizumab in a single institution in France. The co-primary endpoints were overall survival (OS) and progression-free survival (PFS) at 6 months. Secondary endpoints were objective response rate (ORR), duration of response (DOR), disease control rate (DCR) and safety. RESULTS: 78 patients were included in the study. The median OS was 7.3 months (3.8-12.2). The estimated OS rate at 6 months was 61.5% (50.5-72.6). The median PFS was 3.1 months (1.4-7.2). The estimated PFS rate at 6 months was 42.3% (31.1-53.5). The best ORR was 35.9%. The mean DOR was 95.5 days. The DCR was 30.8%. The most common treatment-related adverse events (AEs) of any grade were fatigue (46.2%), diarrhea (11.5%), pruritus (10.3%) and nausea (9.0%). There were no grade 3 AEs that occurred with an incidence of 5% or more. CONCLUSION: Our results confirmed those of randomized clinical trials concerning the treatment with pembrolizumab in patients with advanced UC that progressed after platinum-based chemotherapy.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".