LLM-Generated Lay-Language Protocols for Molecular Tumor Board Patients: Evaluation of Quality and Clinical Usability

作者：Tabea M. G. Pakull, Noëlle Bender, Sven Benson, Anke Fleischhauer, Mohammad Alsara, Tanja Gromke, Thomas Hilser, Katharina Kaminski, Michael Pogorzelski, Nicola Prasuhn, Vivian Rosery, Dirk Schadendorf, Martin Schüler, Marcel Wiesweg, Gregor Zaun, Peter A. Horn, Christoph M. Friedrich, Ina Pretzell · 发表于：Journal of Medical Internet Research · 年份：2026 · DOI：10.2196/99136 · 研究领域：Artificial Intelligence in Healthcare and Education、Cancer Genomics and Diagnostics、Topic Modeling

Background: Molecular Tumor Boards (MTBs) generate highly technical recommendations. The language used in their protocols is rarely accessible to patients. Lay-language patient protocols could support patient-clinician communication, yet manual production is difficult to sustain in high-volume oncology settings. Large language models (LLMs) may offer scalable drafting assistance, yet clinical usability remains largely uninvestigated under real-world deployment constraints. Existing evaluations rely predominantly on synthetic data or closed-source models that are incompatible with strict data protection requirements. Objective: This study evaluated whether open-weight LLMs can provide clinically usable drafting support for German MTB patient protocols under real-world deployment constraints and developed a transferable evaluation framework for patient-facing text generation. Methods: Eight open-weight LLMs were evaluated under zero-shot (A1) and one-shot (A2) prompting with constrained decoding, which ensures section-schema compliance. Automatic evaluation used ROUGE-1 (Recall-Oriented Understudy for Gisting Evaluation), BERTScore-F1 (Bidirectional Encoder Representations From Transformers Score), Wiener Sachtextformel version 4, and DistilBERT (Distilled Version of Bidirectional Encoder Representations From Transformers)-based complexity using a corpus of 316 MTB protocols and 47 expert-written patient protocols. For expert evaluation, 7 medical oncologists evaluated 50 proto...