Can Artificial Intelligence Counsel Men with Testicular Cancer? A Validated Comparison of ChatGPT, Gemini and Claude

Background/Objectives: Large language models (LLMs) such as ChatGPT, Gemini and Claude are increasingly used by patients to research new diagnoses, including testicular cancer. The aim of this study was to evaluate and compare the quality of responses generated by these three platforms to patient-facing frequently asked questions on testicular cancer, including a focused evaluation of fertility and sexual health questions. Methods: Fifteen questions were developed from established patient education resources and refined by senior urology consultant review. Each question was posed to ChatGPT, Gemini and Claude using a standardised patient-perspective prompt. The 45 responses were de-identified, randomised and assessed in a single consensus meeting by a urology panel using the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool. Comparative analysis used the Friedman test with Bonferroni-corrected pairwise Wilcoxon signed-rank testing. Results: All three models produced moderate quality responses, with a mean total QAMAI score of 21.8 for ChatGPT, 22.4 for Claude, and 22.1 for Gemini (Friedman p = 0.246). Clarity differed significantly between models (adjusted p = 0.022), with Claude and Gemini outperforming ChatGPT. In the fertility and sexual health domain, Claude (24.0) and Gemini (23.0) outperformed ChatGPT (19.7). No response from any model spontaneously cited references or directed the reader to external resources. Conclusions: ChatGPT, Gemini and Claude deliver broadly equivalent overall quality on patient-facing testicular cancer questions, with inter-model differences in clarity and in the fertility and sexual health domain. The absence of source citation is a clinically relevant limitation. These tools should be regarded as a supplement to, rather than a substitute for, specialist counselling.