“AI-ASSISTED RENAL TUMOR MANAGEMENT: A COMPARATIVE EVALUATION OF CHATGPT AND MULTIDISCIPLINARY TEAM DECISIONS” - khan, Jawad; Malik Furqan Mahmood; Muhammad Saleem; Mudassar Abbas; Saddam Hussain; Syed Muhammad Ali Hasnu; Abdul Basit Khan; Hifza Jadoon; Mezhgan Kiwan (Journal of Ayub Medical College Abbottabad, 2026)
Abstract Background: Renal tumors, including renal cell carcinoma (RCC), often require complex and personalized decision-making processes, typically achieved through multidisciplinary team (MDT) discussions. With advancements in artificial intelligence (AI), tools like ChatGPT have the potential to aid decision-making. This study evaluates ChatGPT’s ability to align its recommendations with MDT decisions in renal tumor management. Methods: This retrospective study analyzed 13 renal tumor cases discussed by MDTs. Tumor classifications were based on the TNM staging system, including T1a, T1b, T2, T3/T4, and metastatic RCC. Treatment recommendations—partial nephrectomy, radical nephrectomy, systemic therapy, and surveillance—were generated by ChatGPT using the European Association of Urology (EAU) guidelines. Concordance with MDT decisions was assessed. Results: Localized RCC (T1-T2) accounted for 61.5% of cases, advanced RCC (T3/T4) for 15.4%, and metastatic RCC for 23.1%. Treatment recommendations included partial nephrectomy (23.1%), radical nephrectomy (46.2%), systemic therapy (23.1%), and surveillance (7.7%). ChatGPT demonstrated 100% concordance with MDT decisions across all cases. Conclusion: ChatGPT’s ability to align with MDT decisions underscores its potential as a supplementary tool in renal tumor management. However, human oversight is essential to account for patient-specific and contextual factors. Larger studies are required to validate these findings and refine AI integration into clinical workflows.