S1408
Interdisciplinary - Health economics & health services research
ESTRO 2026
EHR hospital records for relevant GI conditions using ICD-10 codes within two years post-radiotherapy. Three endpoints were assessed: proctitis, proctitis and/or haemorrhage, and combined event (proctitis and/or haemorrhage and/or fistula). Rectal DVH features were quantified by isotropically resampling DICOM dose cubes to a 1 mm3 grid, converting to EQD2 ( α / β = 3 Gy), and extracting values for the 3 mm- thick rectal wall. High-dose DVH parameters (V50-V70) were evaluated with all hospital events hypothesised to correspond to grade ≥ 3 toxicity [3]. DVH distributions in event and non-event groups were compared using the Mann-Whitney U test, with p- values corrected for multiple comparisons via the Benjamini-Hochberg FDR method. Results: Overall, 83 patients (6%) had proctitis, 11 (1%) haemorrhage, and 2 (<1%) fistula; 91 (7%) had either proctitis or haemorrhage, and 93 (7%) had the combined event. All high-dose V-metrics were significantly higher in the event group, with median rectal volumes receiving ≥ 50-70 Gy increasing by 1.4- 2.2 % compared to non-events, as illustrated in Figure 1, which demonstrates a consistent upward trend across all high dose levels and a clear dose-response relationship between rectal exposure and GI toxicity. Figure 2 shows the V70 distribution for the combined event endpoint, where the event group exhibits a rightward shift and elevated median dose.
Conclusion: The detection of a robust, statistically significant median shift in high-dose rectal volume between toxicity groups validates the sensitivity of using endpoints extracted from large-scale multi-modal EHR data in PROSECCA. This sensitivity to known dosimetric risk factors supports the use of routine clinical population-based dataset for large-scale, personalised radiotherapy modelling, complementing knowledge from prospective studies and RCTs, and addressing the gap left by missing standardised toxicity data such as CTCAE/RTOG. References: [1] Lievens Y, Borras JM, Grau C, Aggarwal A. Value-based radiotherapy: A new chapter of the ESTRO-HERO project. Radiotherapy and Oncology 2021;160:236–9. https://doi.org/10.1016/j.radonc.2021.05.007.[2] Marks LB, Yorke ED, Jackson A, Ten Haken RK, Constine LS, Eisbruch A, et al. Use of Normal Tissue Complication Probability Models in the Clinic. Int J Radiat Oncol Biol Phys 2010;76. https://doi.org/10.1016/j.ijrobp.2009.07.1754.[3] Cicchetti A, Fiorino C, Ebert MA, Iacovacci J, Kennedy A, Joseph DJ, et al. Validation of prediction models for radiation-induced late rectal bleeding: Evidence from a large pooled population of prostate cancer patients. Radiotherapy and Oncology 2023;183. https://doi.org/10.1016/j.radonc.2023.109628. Keywords: prostate cancer, electronic healthcare record Digital Poster 2933 Optimal radiotherapy utilisation and fractionation for lung cancer – an update Jessica Y Lin 1,2 , Anzela Anzela 1,2 , Karen Wong 1,2 , Shalini K Vinod 1,2 , Eric Hau 3,4 , Mei Ling Yap 1,2 , Geoff P Delaney 1,2 1 Collaboration for Cancer Outcomes, Research and Evaluation, Ingham Institute for Applied Medical Research, Liverpool, Australia. 2 Liverpool and Macarthur Cancer Therapy Centre, South Western Sydney Local Health District, Liverpool, Australia. 3 Western Sydney Radiation Oncology Network,
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