Evaluating ChatGPT-4o as a decision support tool in multidisciplinary sarcoma tumor boards: heterogeneous performance across various specialties

Abstract

Background and objectives: Since the launch of ChatGPT in 2023, large language models have attracted substantial interest to be deployed in the health care sector. This study evaluates the performance of ChatGPT-4o as a support tool for decision-making in multidisciplinary sarcoma tumor boards. Methods: We created five sarcoma patient cases mimicking real-world scenarios and prompted ChatGPT-4o to issue tumor board decisions. These recommendations were independently assessed by a multidisciplinary panel, consisting of an orthopedic surgeon, plastic surgeon, radiation oncologist, radiologist, and pathologist. Assessments were graded on a Likert scale from 1 (completely disagree) to 5 (completely agree) across five categories: understanding, therapy/diagnostic recommendation, aftercare recommendation, summarization, and support tool effectiveness. Results: The mean score for ChatGPT-4o performance was 3.76, indicating moderate effectiveness. Surgical specialties received the highest score, with a mean score of 4.48, while diagnostic specialties (radiology/pathology) performed considerably better than the radiation oncology specialty, which performed poorly. Conclusions: This study provides initial insights into the use of prompt-engineered large language models as decision support tools in sarcoma tumor boards. ChatGPT-4o recommendations regarding surgical specialties performed best while ChatGPT-4o struggled to give valuable advice in the other tested specialties. Clinicians should understand both the advantages and limitations of this technology for effective integration into clinical practice.

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