Evaluating AI and Human Expert Decisions in Colorectal Cancer

The goal of this observational study is to evaluate the decision-making consistency between large language models (LLMs) and expert multidisciplinary teams (MDTs) in adult patients diagnosed with colorectal cancer who underwent MDT consultation between January 2023 and December 2024. The main questions it aims to answer are: How consistent are the treatment decisions generated by LLMs compared to actual MDT decisions? Do different LLMs (e.g., ChatGPT, DeepSeek) show varying levels of agreement with expert recommendations? What clinical factors contribute to differences between AI-generated and human expert decisions? Researchers will compare the AI-generated treatment recommendations with real-world MDT decisions using anonymized patient records to see if LLMs can reliably support clinical decision-making in oncology. Participants will: Have their de-identified clinical data (e.g., imaging, pathology, MDT notes) processed through several LLMs Not be contacted or receive any interventions, as this is a retrospective study using existing clinical records only.

NCT Number	NCT07045207
Lead Sponsor	Peking University Cancer Hospital & Institute
Conditions	Colorectal Cancer
Enrollment	1,500 participants
Start Date	2025-07-01
Primary Completion	2026-06-01 (estimated)
Study Completion	2026-06-01 (estimated)
Updated on ClinicalTrials.gov	2025-07-01