Guiding first-line treatment decisions in advanced urothelial carcinoma: a global survey
Bibliographic record
Abstract
BACKGROUND: Enfortumab vedotin combined with pembrolizumab (EV-P) has become the new standard first-line therapy for patients with advanced urothelial carcinoma (aUC), based on its superior efficacy over platinum-based chemotherapy. As this regimen is increasingly adopted in routine care, treatment decisions may often occur in sites without dedicated genitourinary oncology expertise. This global survey aimed to explore how physicians perceive clinical factors that may influence the safe and effective use of EV-P in daily practice. MATERIAL AND METHODS: A panel of international physicians with experience in treating patients with genitourinary cancers developed a 17-question survey addressing practice settings, experience in managing aUC, and clinical considerations relevant to the use of EV-P. The participants were recruited through a network-based convenience sampling method. The responses were descriptively analyzed. RESULTS: A total of 201 genitourinary physicians from 32 countries completed the questionnaire. The most frequently cited potential absolute contraindications were sensory or motor neuropathy grade ≥2 (64.2%), ECOG-PS ≥3 (59.2%), and non-urothelial component >50% of the tissue sample (59.2%). Other notable concerns included severe corneal/retinal abnormalities, HbA1c >11%, severe skin comorbidities, liver impairment grade ≥2, and dialysis dependence. CONCLUSIONS AND RELEVANCE: This survey provides practical insights into real-world physician perspectives on patient selection for EV-P. The findings highlight the need for guidance to support personalized risk assessment, facilitate early identification of patients who may require enhanced monitoring, and optimize safe integration of EV-P into clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".