BACKGROUND AND PURPOSE: Pediatric radiotherapy patients and their parents are usually aware of their need for radiotherapy early on, but they meet with a radiation oncologist later in their treatment. Consequently, they search for information online, often encountering unreliable sources. Large language models (LLMs) have the potential to serve as an educational pretreatment tool, providing reliable answers to their questions. We aimed to evaluate the responses provided by generative pre-trained transformers (GPT), the most popular subgroup of LLMs, to questions about pediatric radiation oncology. MATERIALS AND METHODS: We collected pretreatment questions regarding radiotherapy from patients and parents. Responses were generated using GPT-3.5, GPT-4, and fine-tuned GPT-3.5, with fine-tuning based on pediatric radiotherapy guides from various institutions. Additionally, a radiation oncologist prepared answers to these questions. Finally, a multi-institutional group of nine pediatric radiotherapy experts conducted a blind review of responses, assessing reliability, concision, and comprehensibility. RESULTS: The radiation oncologist and GPT-4 provided the highest-quality responses, though GPT-4's answers were often excessively verbose. While fine-tuned GPT-3.5 generally outperformed basic GPT-3.5, it often provided overly simplistic answers. Inadequate responses were rare, occurring in 4% of GPT-generated responses across all models, primarily due to GPT-3.5 generating excessively long responses. CONCLUSIONS: LLMs can be valuable tools for educating patients and their families before treatment in pediatric radiation oncology. Among them, only GPT-4 provides information of a quality comparable to that of a radiation oncologist, although it still occasionally generates poor-quality responses. GPT-3.5 models should be used cautiously, as they are more likely to produce inadequate answers to patient questions.

Department of Economics Ludwig Maximilian University of Munich Geschwister Scholl Platz 1 80539 Munich Germany

Department of Internal Diseases Riga Stradiņš University Dzirciema iela 16 LV 1007 Riga Latvia

Department of Oncology Maria Sklodowska Curie National Research Institute of Oncology Garncarska 11 31 115 Cracow Poland

Department of Radiation Oncology Faculty of Medicine Masaryk University Kamenice 5 625 00 Brno Czech Republic

Department of Radiation Oncology Lower Silesian Center of Oncology Pulmonology and Hematology Hirszfelda 12 53 413 Wroclaw Poland

Department of Radiation Oncology Maria Sklodowska Curie National Research Institute of Oncology Wawelska 15B 02 034 Warsaw Poland

Department of Radiation Oncology Masaryk Memorial Cancer Institute Žlutý kopec 7 656 53 Brno Czech Republic

Department of Radiation Oncology Riga East University Hospital Hipokrāta iela 2 LV 1038 Riga Latvia

Faculty of Medicine and Health Sciences Andrzej Frycz Modrzewski Krakow University Gustawa Herlinga Grudzińskiego 1 30 705 Cracow Poland

ifo Institute Poschinger Straße 5 81679 Munich Germany

Oncology Institute Lithuanian University of Health Sciences A Mickevičiaus g 9 LT 44307 Kaunas Lithuania

Radiotherapy Department Maria Sklodowska Curie National Research Institute of Oncology Wybrzeże Armii Krajowej 15 44 100 Gliwice Poland

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