aceMachine learning integrated explainable artificial intelligence in predicting toxicities of enfortumab vedotin in urothelial carcinoma: an exploratory study
Background Enfortumab vedotin (EV) therapy for advanced urothelial carcinoma is limited by adverse events (AEs). Early identification of high-risk patients is needed. This proof-of-concept study evaluated whether machine learning (ML) with explainable AI (SHAP) could predict EV toxicities using real-world data. Research design and methods Data from 542 patients (51 centers, 24 countries) were analyzed. Six outcomes were predicted including grade 3-4 AEs. Four ML algorithms were trained on an 80% split and tested…
The models are exploratory, built on small event counts with no external validation, so they cannot yet be used in clinics to reduce side effects from enfortumab vedotin.
Findings are preliminary and hypothesis-generating due to single train-test split, small event counts, and lack of external validation, which precludes clinical use and requires prospective validation.
Evidence
- Peer-reviewedExpert Review of Anticancer Therapy2026-09-16
How should this claim be treated?
Truvace Impact Record TRV-2026-1121, v2: “Machine learning integrated explainable artificial intelligence in predicting toxicities of enfortumab vedotin in urothelial carcinoma: an exploratory study.” Truvace, 2026-11-04. /record/TRV-2026-1121 (accessed at citation time). sha256 d32ea95548654cb3…
Calibration history
Every change to this record since certification, in the open.
Editorial pass: sharper headline; gain/problem restated as concrete outcomes; refiled trace to p_space (gain activity_only, problem outcome).
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1121 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.