AI meets informed consent: a new era for clinical trial communication

作者：Michael R. Waters · 发表于：JNCI Cancer Spectrum · 年份：2025 · DOI：10.1093/jncics/pkaf028 · 被引用次数：20 · 研究领域：Artificial Intelligence in Healthcare and Education、Patient-Provider Communication in Healthcare、Ethics in Clinical Research

Clinical trials are fundamental to evidence-based medicine, providing patients with access to novel therapeutics and advancing scientific knowledge. However, patient comprehension of trial information remains a critical challenge, as registries like ClinicalTrials.gov often present complex medical jargon that is difficult for the general public to understand. While initiatives such as plain-language summaries and multimedia interventions have attempted to improve accessibility, scalable and personalized solutions remain elusive. This study explores the potential of Large Language Models (LLMs), specifically GPT-4, to enhance patient education regarding cancer clinical trials. By leveraging informed consent forms from ClinicalTrials.gov, the researchers evaluated 2 artificial intelligence (AI)-driven approaches-direct summarization and sequential summarization-to generate patient-friendly summaries. Additionally, the study assessed the capability of LLMs to create multiple-choice question-answer pairs (MCQAs) to gauge patient understanding. Findings demonstrate that AI-generated summaries significantly improved readability, with sequential summarization yielding higher accuracy and completeness. MCQAs showed high concordance with human-annotated responses, and over 80% of surveyed participants reported enhanced understanding of the author's in-house BROADBAND trial. While LLMs hold promise in transforming patient engagement through improved accessibility of clinical trial info...