Back to Search Start Over

Evaluation of ChatGPT-4's Performance in Therapeutic Decision-Making During Multidisciplinary Oncology Meetings for Head and Neck Squamous Cell Carcinoma.

Authors :
Alami K
Willemse E
Quiriny M
Lipski S
Laurent C
Donquier V
Digonnet A
Source :
Cureus [Cureus] 2024 Sep 06; Vol. 16 (9), pp. e68808. Date of Electronic Publication: 2024 Sep 06 (Print Publication: 2024).
Publication Year :
2024

Abstract

Objectives First reports suggest that artificial intelligence (AI) such as ChatGPT-4 (Open AI, ChatGPT-4, San Francisco, USA) might represent reliable tools for therapeutic decisions in some medical conditions. This study aims to assess the decisional capacity of ChatGPT-4 in patients with head and neck carcinomas, using the multidisciplinary oncology meeting (MOM) and the National Comprehensive Cancer Network (NCCN) decision as references. Methods This retrospective study included 263 patients with squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx, and larynx who were followed at our institution between January 1, 2016, and December 31, 2021. The recommendation of GPT4 for the first- and second-line treatments was compared to the MOM decision and NCCN guidelines. The degrees of agreement were calculated using the Kappa method, which measures the degree of agreement between two evaluators. Results ChatGPT-4 demonstrated a moderate agreement in first-line treatment recommendations (Kappa = 0.48) and a substantial agreement (Kappa = 0.78) in second-line treatment recommendations compared to the decisions from MOM. A substantial agreement with the NCCN guidelines for both first- and second-line treatments was observed (Kappa = 0.72 and 0.66, respectively). The degree of agreement decreased when the decision included gastrostomy, patients over 70, and those with comorbidities. Conclusions The study illustrates that while ChatGPT-4 can significantly support clinical decision-making in oncology by aligning closely with expert recommendations and established guidelines, ongoing enhancements and training are crucial. The findings advocate for the continued evolution of AI tools to better handle the nuanced aspects of patient health profiles, thus broadening their applicability and reliability in clinical practice.<br />Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Jules Bordet Institute issued approval CE3827. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.<br /> (Copyright © 2024, Alami et al.)

Details

Language :
English
ISSN :
2168-8184
Volume :
16
Issue :
9
Database :
MEDLINE
Journal :
Cureus
Publication Type :
Academic Journal
Accession number :
39376890
Full Text :
https://doi.org/10.7759/cureus.68808