ChatGPT in glioma patient adjuvant therapy decision making: ready to assume the role of a doctor in the tumour board?

Abstract

Introduction ChatGPT, a novel AI-based chatbot, sparked a lot of interest in the scientific community. Complex central CNS tumour cases require multidisciplinary expert recommendations that incorporate multimodal disease information. Thus, the potential of ChatGPT to integrate comprehensive treatment information may be of tremendous benefit for CNS tumour decision-making. We evaluated the ChatGPT recommendations for glioma management by a panel of CNS tumour experts. Methods We randomly selected 10 patients with primary CNS gliomas discussed at our institution's Tumour Board. Patients' clinical status, surgical, imaging, and immuno-pathology-related information was provided to ChatGPT and seven CNS tumour experts. The chatbot was asked to give the most likely diagnosis, the adjuvant treatment choice, and the regimen while considering the patient's functional status. The experts rated the AI-based recommendations from 0 (complete disagreement) to 10 (complete agreement). An intraclass correlation agreement (ICC) was used to measure the inter-rater agreement. Results Eight patients (80%) met the criteria for glioblastoma and two (20%) were low-grade gliomas. The experts rated the quality of ChatGPT recommendations as poor for diagnosis (median 3, IQR 1-7.8, ICC 0.9, 95% CI 0.7-1.0), good for treatment recommendation (7, IQR 6-8, ICC 0.8, 95% CI 0.4-0.9), good for therapy regimen (7, IQR 4-8, ICC 0.8, 95% CI 0.5-0.9), moderate for functional status consideration (6, IQR 1-7, ICC 0.7, 95% CI 0.3-0.9), and moderate for overall agreement with the recommendations (5, IQR 3-7, ICC 0.7, 95% CI 0.3-0.9). No differences were observed between the glioblastomas and low-grade glioma ratings. Conclusions ChatGPT performed poorly in classifying glioma types but was good for adjuvant treatment recommendations as evaluated by CNS Tumour Board experts. Even though the ChatGPT lacks the precision to replace expert opinion, it may become a promising tool to supplement experts, especially in low-resource settings.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study did not receive any funding

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The work was approved by the Regional Ethics Committee of Geneva

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Data Availability

All data produced in the present study are available upon reasonable request to the authors.

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