ESTRO 2025 - Abstract Book

S1383

Clinical - Lung

ESTRO 2025

Conclusion: With the increasing application of artificial intelligence in cancer research, machine learning is poised to play a significant role in prognostication and decision-making. Our results demonstrate that the proposed pipeline is highly effective for pCR prediction, indicating its robustness in capturing relevant information from EHRs even without the combination of other clinical information.

Keywords: radiomics, precision medicine, AI

3119

Digital Poster Psychological Impact of Lung Cancer Diagnosis amina majdi 1,2 , Chadia Ezzouitina 1,2 , fatima zahra chraa 1,2 , sara smiti 1,2 , Laraichi Rachida 1,2 , Amine Lachgar 1,2 , karima nouni 1,2 , hanan el kacemi 1,2 , Tayeb kebdani 1,2 , Khalid hassouni 1,2 1 Radiotherapy, National Institute of Oncology, Rabat, Morocco. 2 Faculty of medicine and pharmacy, Medicine, Rabat, Morocco Purpose/Objective: Receiving a lung cancer diagnosis represents a life-altering and emotionally challenging event. This study investigates the emotional, cognitive, and behavioral responses of patients to the announcement of their diagnosis, emphasizing its psychological effects and progression over time. Material/Methods: From 2020 to 2022, a total of 244 lung cancer patients treated at the National Oncology Institute in Rabat participated in this study. Patients completed questionnaires assessing their emotional and psychological states. Key metrics included: • Anxiety and depression levels (measured using the Hamilton Anxiety Scale [HAM-A] and Beck Depression Inventory [BDI]). • Quality of life (evaluated via the SF-36 Health-Related Quality of Life questionnaire). Assessments were conducted at three time points: 1. Upon diagnosis announcement.