S1407
Interdisciplinary - Health economics & health services research
ESTRO 2026
the ESTRO-HERO model to incorporate PT costing. References: Weber, D. C., Abrunhosa-Branquinho, A., Bolsi, A., Kacperek, A., Dendale, R., Geismar, D., ... & Grau, C. (2017). Profile of European proton and carbon ion therapy centers assessed by the EORTC facility questionnaire. Radiotherapy and Oncology, 124(2), 185-189. Keywords: particle therapy, survey , current practice Validating radiotherapy endpoints from real-world electronic healthcare records in the PROSECCA study: a nationwide prostate cancer study Zhuolin Yang 1,2 , Sarah Elliot 1,3 , David J Noble 1,4 , Archie MacNair 4 , Ewen M Harrison 3 , George Beckett 5 , Alasdair Rutherford 6 , Duncan B McLaren 1,4 , William H Nailon 7,2 1 Edinburgh Cancer Research, CRUK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom. 2 Institute for Imaging, Data and Communications, School of Engineering, University of Edinburgh, Edinburgh, United Kingdom. 3 Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom. 4 Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, United Kingdom. 5 Edinburgh Parallel Digital Poster 2850 Computing Centre, University of Edinburgh, Edinburgh, United Kingdom. 6 Department of Radiotherapy Physics, Beatson West of Scotland Cancer Centre, Glasgow, United Kingdom. 7 Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, United Kingdom Purpose/Objective: Randomised controlled trails (RCTs) remain the gold standard for evidence generation but are expensive, slow, and often outdated at reporting. Maximising information derived from every treated patient has therefore become an urgent priority [1]. The PROSECCA study (improving radiotherapy in PROState cancer using EleCtronic population-based healthCAre data) interrogates routine clinical electronic healthcare (EHR) data to identify predictive biomarkers of radiation response in prostate cancer. This work aimed to test the feasibility of deriving radiobiologically meaningful toxicity endpoints from large-scale, multi-modal EHR data, by correlating EHR- derived events with validated rectal DVH predictors of toxicity [2]. Material/Methods: Data for this analysis was taken from one of five participating PROSECCA centres between 2020 and 2023 (N = 1390). Binary event status was defined by
Conclusion: These findings suggest that, at an operational and resource level, PT largely aligns with EBRT, thus enabling the development of a unified and comparable tool for radiation treatment cost estimation. These data will inform the adaptation of
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