Generative artificial intelligence as a source of breast cancer information for patients: Proceed with caution

Abstract

BACKGROUND: This study evaluated the accuracy, clinical concordance, and readability of the chatbot interface generative pretrained transformer (ChatGPT) 3.5 as a source of breast cancer information for patients. METHODS: Twenty questions that patients are likely to ask ChatGPT were identified by breast cancer advocates. These were posed to ChatGPT 3.5 in July 2023 and were repeated three times. Responses were graded in two domains: accuracy (4-point Likert scale, 4 = worst) and clinical concordance (information is clinically similar to physician response; 5-point Likert scale, 5 = not similar at all). The concordance of responses with repetition was estimated using intraclass correlation coefficient (ICC) of word counts. Response readability was calculated using the Flesch Kincaid readability scale. References were requested and verified. RESULTS: The overall average accuracy was 1.88 (range 1.0-3.0; 95% confidence interval [CI], 1.42-1.94), and clinical concordance was 2.79 (range 1.0-5.0; 95% CI, 1.94-3.64). The average word count was 310 words per response (range, 146-441 words per response) with high concordance (ICC, 0.75; 95% CI, 0.59-0.91; p < .001). The average readability was poor at 37.9 (range, 18.0-60.5) with high concordance (ICC, 0.73; 95% CI, 0.57-0.90; p < .001). There was a weak correlation between ease of readability and better clinical concordance (-0.15; p = .025). Accuracy did not correlate with readability (0.05; p = .079). The average number of references was 1.97 (range, 1-4; total, 119). ChatGPT cited peer-reviewed articles only once and often referenced nonexistent websites (41%). CONCLUSIONS: Because ChatGPT 3.5 responses were incorrect 24% of the time and did not provide real references 41% of the time, patients should be cautioned about using ChatGPT for medical information.

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