S1155
Clinical - Urology
ESTRO 2026
association with the BED was present, with significant association in the adaptive ultrahypofractionated course that require validation. These results highlight the potential of radiomics to serve as biomarkers for dose-related tissue response and may potentially support adaptive decision-making in HyperSight™- guided radiotherapy. References: (1) DOI: 10.1158/0008-5472.CAN-18-0125 Keywords: aRT, prostate, Radiomics Pooled analysis of observational studies in prostate cancer: quality of life changes in 1723 patients, 6 months after initiation of triptorelin Igor Latorzeff 1 , Pierre Mongiat-Artus 2 , Nathalie Pello- Leprince-Ringuet 3 , Marie-Cécile Fournier 4 , Stéphane Droupy 5 1 Radiation Oncology department, Groupe Orion, Clinique Pasteur, Toulouse, France. 2 Urology department, Saint-Louis Hospital, Université Paris Cité, Poster Discussion 855 Paris, France. 3 Medical department, Ipsen, Paris, France. 4 Biometry department, Ipsen, Paris, France. 5 Urology Andrology department, CHU Caremeau, Nîmes, France Purpose/Objective: Little is known about impact of androgen deprivation therapy (ADT), like triptorelin on health-related quality of life (HRQoL) in real life. The purpose of PATRIS study was to explore the impact of triptorelin on HRQoL in a large population of patients after a 6-month treatment. Material/Methods: Individual data from 3 observational studies conducted prospectively in France (FOCUS 2008-10, EQUINOXE 2015-17, TALISMAN 2020-22) were pooled, with patients having histologically confirmed prostate cancer, and data on HRQoL evaluated with QLQ-PR25 questionnaire at baseline and after a 6-month treatment with triptorelin. Data were anonymized to allow patients privacy. Primary objective was to analyze the impact of triptorelin on HRQoL, evaluated with QLQ-PR25, hormonal treatment-related symptoms (HTRS) and sexual activity (SA) subscales, after a 6-month follow-up (6mFU). Secondary objectives included changes of the other QLQ-PR25 subscales (urinary symptoms, incontinence aid, bowel symptoms, sexual functioning) and identification of parameters associated with score changes of HTRS and SA through a multiple linear regression model. Results: The final analysis included 1723 patients. Main baseline parameters descriptive statistics are presented in Table 1. Median PSA level [Q1,Q3] was
prospectively included for analysis. BED of the mean dose was computed per fraction and patient for the non-hollow organ volumes of interest (VOIs) prostate & seminal vesicles ( α / β = 2 Gy) and penile bulb & bilateral femoral heads ( α / β = 3 Gy) and were summed across all fractions. From HyperSight™ CBCTs, 114 radiomic features were extracted with LIFEx-25.06.1 (1). Percentage changes were determined between the last and the first fraction (UHFX fx5 vs. fx1; MHFX fx20 vs. fx1) and at matched intermediate fractions with similar accumulated BED (UHFX fx2 vs. fx1; MHFX fx7 vs. fx1), then aggregated to a cumulative change per patient & VOI. The association between BED and cumulative change was quantified by Pearson correlation and examined in a rank-based mixed- effects model. Results:
In the rank-based mixed-effects model, accounting for radiomic feature groups, higher BED was linked to a greater cumulative interfraction percentage change ( β =0.074, p=0.041). Analyzing the regimens separately, the association was present in UHFX ( β =0.10, p=0.023) but not in MHFX ( β =0.013, p=0.84); the difference in effect size between the regimens was not statistically significant (p=0.26). At the feature level, in the prostate the metric GLSZM_SmallZoneHighGreyLevelEmphasis showed a strong correlation with BED (r= − 0.72) and remained significant after correction for multiple comparisons; we observed other high correlations, but these did not meet statistical significance. Figures 1–2 display BED distributions by VOI and correlation heatmaps for prostate and seminal vesicle. Conclusion: Radiomic features can capture dose-related tissue changes during prostate radiotherapy. An overall
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