Artificial Intelligence (ChatGPT-4o) in Adjuvant Treatment Decision-Making for Stage II Colon Cancer: A Comparative Analysis with Clinician Recommendations and NCCN/ESMO Guidelines

The role of artificial intelligence (AI) in oncology decision-making is rapidly expanding, yet its concordance with clinician recommendations and established guidelines remains unclear. This study evaluates the agreement between AI-generated adjuvant therapy recommendations for stage II colon cancer, clinician decisions, and international guidelines (NCCN, ESMO). We conducted a retrospective comparative analysis of 197 stage II colon cancer patients treated at Hacettepe University between 2014 and 2023. AI-generated recommendations (ChatGPT-4o) were compared with clinician decisions and NCCN/ESMO guidelines. Concordance rates were analyzed using Cohen’s kappa and McNemar’s test. Clinician adherence was highest with NCCN (89.8%) and ESMO (84.8%) guidelines. AI recommendations showed moderate agreement with clinician decisions (65.0%, κ= 0.47). Statistically significant differences were observed between AI and clinical practice (p< 0.001), suggesting AI’s more conservative approach. While AI demonstrates potential as a clinical decision-support tool, its moderate alignment with real-world decisions highlights the need for further refinement. Future improvements in AI interpretability, real-world validation, and clinician-AI collaboration are essential for its effective integration into oncology practice. Keywords: Artificial Intelligence, Colon Cancer, Adjuvant treatment

Authors

Publication Details

Journal
International Journal of Hematology and Oncology
Published
2025-03-30
DOI
https://doi.org/10.4999/uhod.258149
Citations
3
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
4.08
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article

Artificial Intelligence (ChatGPT-4o) in Adjuvant Treatment Decision-Making for Stage II Colon Cancer: A Comparative Analysis with Clinician Recommendations and NCCN/ESMO Guidelines

Fatih KUŞ
3 citations
International Journal of Hematology and Oncology
Radiomics and Machine Learning in Medical Imaging
4.08
article

Artificial Intelligence (ChatGPT-4o) in Adjuvant Treatment Decision-Making for Stage II Colon Cancer: A Comparative Analysis with Clinician Recommendations and NCCN/ESMO Guidelines

Fatih KUŞ
article en
3 citations

Abstract

The role of artificial intelligence (AI) in oncology decision-making is rapidly expanding, yet its concordance with clinician recommendations and established guidelines remains unclear. This study evaluates the agreement between AI-generated adjuvant therapy recommendations for stage II colon cancer, clinician decisions, and international guidelines (NCCN, ESMO). We conducted a retrospective comparative analysis of 197 stage II colon cancer patients treated at Hacettepe University between 2014 and 2023. AI-generated recommendations (ChatGPT-4o) were compared with clinician decisions and NCCN/ESMO guidelines. Concordance rates were analyzed using Cohen’s kappa and McNemar’s test. Clinician adherence was highest with NCCN (89.8%) and ESMO (84.8%) guidelines. AI recommendations showed moderate agreement with clinician decisions (65.0%, κ= 0.47). Statistically significant differences were observed between AI and clinical practice (p< 0.001), suggesting AI’s more conservative approach. While AI demonstrates potential as a clinical decision-support tool, its moderate alignment with real-world decisions highlights the need for further refinement. Future improvements in AI interpretability, real-world validation, and clinician-AI collaboration are essential for its effective integration into oncology practice. Keywords: Artificial Intelligence, Colon Cancer, Adjuvant treatment

International Journal of Hematology and Oncology
Openalex Percentile: Top 7%
Radiomics and Machine Learning in Medical Imaging
4.08
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