Split-Dose Cisplatin Use, Eligibility Criteria, and Drivers for Treatment Choice in Patients with Locally Advanced or Metastatic Urothelial Carcinoma: Results of a Large International Physician Survey
Bibliographic record
Abstract
BACKGROUND: For many decades, gemcitabine + cisplatin has been a preferred and accepted treatment option for patients with urothelial cancer (UC). In patients ineligible for standard-dose cisplatin, split-dose cisplatin is a promising alternative. This study aimed to provide insights into the use of split-dose cisplatin and factors influencing treatment choice. METHODS: Between January and March 2024, an international cross-sectional survey was carried out, which involved oncologists and urologists treating patients with locally advanced/metastatic UC (la/mUC) in Australia, Brazil, Canada, France, Germany, India, Italy, Spain, the UK, and the USA. Demographics, practice patterns, and clinical parameters influencing treatment choice were collected. RESULTS: on days 1 and 8 of 21-day cycles (57%). Most respondents (64%) were comfortable prescribing split-dose cisplatin to otherwise fit patients with a creatinine clearance ≥40 mL/min. Standard- and split-dose cisplatin were preferred regimens for otherwise fit patients with creatinine clearance of 45-60 mL/min. CONCLUSIONS: This large international survey demonstrates the extensive use of split-dose cisplatin in patients with la/mUC. Responses indicate that split-dose cisplatin is administered to patients in clinical practice with a wider range of creatinine clearance, performance status, and comorbidities than suggested for standard-dose cisplatin. Results highlight the need to evaluate split-dose cisplatin prospectively and establish consensus guidelines for its use, especially in patients unfit for standard-dose cisplatin.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".