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

artificial intelligence chatgpt-4 ent - ear nose and throat head and neck squamous cell carcinoma (hnscc) multidisciplinary oncologic meeting oral oncology

Journal

Cureus
ISSN: 2168-8184
Titre abrégé: Cureus
Pays: United States
ID NLM: 101596737

Informations de publication

Date de publication:
Sep 2024
Historique:
accepted: 04 09 2024
medline: 8 10 2024
pubmed: 8 10 2024
entrez: 8 10 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 39376890
doi: 10.7759/cureus.68808
pmc: PMC11456411
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e68808

Informations de copyright

Copyright © 2024, Alami et al.

Déclaration de conflit d'intérêts

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.

Auteurs

Kenza Alami (K)

Otolaryngology, Jules Bordet Institute, Bruxelles, BEL.

Esther Willemse (E)

Surgical Oncology, Jules Bordet Institute, Bruxelles, BEL.

Marie Quiriny (M)

Surgical Oncology, Jules Bordet Institute, Bruxelles, BEL.

Samuel Lipski (S)

Surgical Oncology, Jules Bordet Institute, Bruxelles, BEL.

Celine Laurent (C)

Otolaryngology - Head and Neck Surgery, Hôpital Ambroise-Paré, Mons, BEL.
Otolaryngology - Head and Neck Surgery, Hôpital Universitaire de Bruxelles (HUB) Erasme Hospital, Bruxelles, BEL.

Vincent Donquier (V)

Surgical Oncology, Jules Bordet Institute, Bruxelles, BEL.

Antoine Digonnet (A)

Surgical Oncology, Jules Bordet Institute, Bruxelles, BEL.

Classifications MeSH