ESTRO 2025 - Abstract Book

S2092

Clinical - Urology

ESTRO 2025

Conclusion: For the first time, we characterised results of the commercially-available MMAI prostate test among contemporary cohorts, observing less reclassification to lower-risk groups among UK intermediate-risk patients compared to the US. Additionally, we found higher rates of patients predicted to benefit from ST-ADT. These hypothesis-generating results may be driven by regional epidemiological and diagnostic practice variations, such as screening protocols and MRI-guided biopsies, and have implications for design of future UK prospective MMAI biomarker and cost effectiveness studies. References: 1. Esteva, A., Feng, J., van der Wal, D. et al. Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. npj Digit. Med. 5, 71 (2022). 2. Spratt DE, Tang S, Sun Y et al. Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer. NEJM Evidence. Published 2023 June 29. 3. Bjartell A, et al. Validation of a digital pathology-based multimodal artificial intelligence (MMAI) prostate biopsy biomarker. Presented at ESMO 2024. 4. C.T.A. Parker et al. External validation of a digital pathology-based multimodal artificial intelligence (MMAI)- derived model in high-risk localized (M0)/metastatic (M1) prostate cancer (PCa). Annals of Oncology. 2023;34 (2_suppl):S956. Keywords: Prostate cancer, biomarkers, digital pathology