Eleanor RalphsC. RaultAlan CallejaM. DaumontJohn R. PenrodMatthew D. ThompsonSue CheesemanMarta Soares2026-03-222026-03-22202410.1080/14796694.2024.2363133https://doi.org/10.1080/14796694.2024.2363133https://andeanlibrary.org/handle/123456789/53433Citaciones: 1This study aimed to develop and evaluate the performance of algorithms for identifying radiotherapy (RT) treatment intent in real-world data from patients with non-metastatic non-small-cell lung cancer (NSCLC). Using data from IPO-Porto hospital (Portugal) and the REAL-Oncology database (England), three algorithms were developed based on available RT information (#1: RT duration, #2: RT duration and type, #3: RT dose) and tested versus reference datasets. Study results showed that all three algorithms had good overall accuracy (91-100%) for patients receiving RT plus systemic anticancer therapy (SACT) and algorithms #2 and #3 also had good accuracy (>99%) for patients receiving RT alone. These algorithms could help classify treatment intent in patients with NSCLC receiving RT with or without SACT in real-world settings where intent information is missing/incomplete.enMedicineRadiation therapyLung cancerOncologyInternal medicineDuration (music)article