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Evaluating the Role of Artificial Intelligence in Enhancing Multidisciplinary Team Decisions for Breast Cancer
Merve Tokoçin1, Turan Pehlivan1, Selçuk Cin2
1Department of General Surgery, University of Health Sciences Türkiye, İstanbul Bağcılar Training and Research Hospital, İstanbul, Türkiye.
Objective:
Multidisciplinary teams (MDTs) are essential for optimizing breast cancer treatment, yet the role of general-purpose artificial intelligence (AI), such as ChatGPT, in supporting these teams remains underexplored. This study compared ChatGPT versions 3.5 and 4 with a hospital-based MDT in making treatment and follow-up recommendations, using St. Gallen, European Society for Medical Oncology, National Comprehensive Cancer Network, and American Society of Clinical Oncology guidelines as a reference.
Materials And Methods:
A retrospective analysis of 100 consecutive breast cancer patients diagnosed between January 2023 and January 2024 at a training hospital in İstanbul, Türkiye, was conducted. The MDT provided consensus-based recommendations, while anonymized patient data were processed by ChatGPT using English prompts based on guideline summaries. Two experienced breast surgeons independently rated recommendation appropriateness on a five-point scale post-treatment, focusing on clinical outcomes, with agreement assessed using weighted Cohen's kappa across cancer stage, molecular subtype, and proliferation index.
Results:
ChatGPT-4 (with a knowledge cut-off of March 2023) demonstrated substantial agreement with the MDT for primary treatments (weighted κ = 0.712), whereas ChatGPT-3.5 showed moderate agreement (κ = 0.600). Agreement for additional recommendations, such as genetic counseling, was lower (GPT-4: κ = 0.398; GPT-3.5: κ = 0.302), with better performance in early-stage and less aggressive subtypes compared to advanced or aggressive cases. Discrepancies were noted in complex or aggressive cases.
Conclusion:
The study suggests ChatGPT, particularly version 4, may serve as a supportive tool for breast cancer teams, especially in early-stage cases, though clinical expertise remains vital for complex scenarios, warranting further research to refine AI integration.
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