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Evaluating the Role of Artificial Intelligence in Enhancing Multidisciplinary Team Decisions for Breast Cancer Management

Year: 2026

Type: article

Abstract: 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.

Source: European Journal of Breast Health

DOI: 10.4274/ejbh.galenos.2026.2025-10-4