ESTRO 2024 - Abstract Book

S994

Clinical - Gynaecology

ESTRO 2024

Vitaliana De Sanctis 18 , Francesca Titone 19 , Clelia Teresa Delle Curti 20 , Alessandra Huscher 21 , Gabriella Ferrandina 22 , Francesco Deodato 1,23 1 Responsible Research Hospital, Radiation Oncology Unit, Campobasso, Italy. 2 Responsible Research Hospital, Medical Physics Unit, Campobasso, Italy. 3 Fondazione Policlinico Universitario Agostino Gemelli IRCCS, UOC di Radioterapia, Dipartimento di Scienze Radiologiche, Radioterapiche ed Ematologiche, Roma, Italy. 4 University of Pisa, Department of Translational Medicine, Division of Radiation Oncology, Pisa, Italy. 5 IEO European Institute of Oncology IRCCS, Department of Radiotherapy, Milano, Italy. 6 S Maria Hospital, Radiation Oncology Center, Terni, Italy. 7 IRCCS San Raffaele Scientific Institute, Department of Radiation Oncology, Milano, Italy. 8 Humanitas Clinical and Research Center-IRCCS, Radiotherapy and Radiosurgery Department, Milano, Italy. 9 Ospedale "Vito Fazzi", radiotherapy Unit, Lecce, Italy. 10 Nuovo Ospedale degli Infermi, UOC Radioterapia, Biella, Italy. 11 Alma Mater Studiorum - Bologna University, Department of Experimental, Diagnostic and Specialty Medicine – DIMES, Bologna, Italy. 12 Fondazione Policlinico Universitario Campus Biomedico, Radiation Oncology Unit, Roma, Italy. 13 Fondazione "Casa Sollievo della Sofferenza", IRCCS, UOC Radioterapia, Foggia, Italy. 14 University of Florence, Radiation Oncology Unit, Oncology Department, Firenze, Italy. 15 Perugia General Hospital, Radiation Oncology Section, Perugia, Italy. 16 Azienda USL Toscana sud est, Arezzo, Radiation Oncology Unit of Arezzo-Valdarno, Arezzo, Italy. 17 Responsible Research Hospital, Medical Oncology Unit, Campobasso, Italy. 18 sapienza University of Rome, Radiotherapy Oncology, Department of Medicine and Surgery and Translational Medicine, Roma, Italy. 19 University Hospital Udine, Department of Radiation Oncology, Udine, Italy. 20 Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, department of Gynecologic Oncology, Milano, Italy. 21 Fondazione Poliambulanza, , U.O. di Radioterapia Oncologica "Guido Berlucchi", Brescia, Italy. 22 Fondazione Policlinico Universitario Agostino Gemelli IRCCS, UOC Ginecologia Oncologica, Dipartimento Scienze della Salute della Donna e del Bambino, Roma, Italy. 23 Università Cattolica del Sacro Cuore Roma, Istituto di radiologia, Roma, Italy

Purpose/Objective:

No accurate prediction models for clinical outcomes of gynaecologic oligometastatic cancer treated with SBRT exist, nor is it clear if attaining a complete response (CR) following SBRT influences oncologic outcomes.

Material/Methods:

A pooled real-world analysis of gynaecological oligometastases in terms of efficacy and clinical outcomes as well an exploratory machine learning model to predict the CR to SBRT were carried out. The clinical CR rate of disease following SBRT was the study main endpoint. The secondary endpoint included the 2-year actuarial local control (LC) rate, defined on a “per-lesion” basis as the disease progression within the SBRT field of irradiation. The machine learning analysis included the selection of reliable prognostic variables and the model training, validation, and testing.

Results:

501 patients from 21 radiation oncology institutions with 846 gynecological metastases were selected for analysis. The majority of lesions were ovarian (449, 53.1%) and uterine metastases (272, 32.1%) in origin, followed by 125 (14.8%) lesions from cervical cancer. Multiple fraction radiotherapy was used to treat 762 metastases (90.1%). The most frequent schedule was 24 Gy in 3 fractions (13.4%). Complete response (CR) was observed in 538 (63.7%) lesions. According to the machine learning model, in uterine cancer, if BED10>78.3Gy, the CR probability was 75.4%; moreover, if volume was less than 13.7cc, the CR probability became 85.1%. In ovarian cancer, if the lesion