ArticleTranslational andrology and urology2026
Filling the information gap: a validated comparison of ChatGPT, Gemini, and Claude for penile cancer patient education.
Article in Translational andrology and urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: ChatGPT, Gemini, and Claude are three large language models (LLMs) increasingly consulted by patients researching a new cancer diagnosis. Penile cancer is rare, stigmatised, and dominated by decisions around organ preservation and sexual function, which makes the quality of patient-facing information particularly consequential. The aim of this study was to assess the quality of responses generated by these LLMs to patient-oriented questions on penile cancer. Methods: Fourteen questions reflecting common patient information needs were adapted from established educational resources and refined by senior urology consultant review. Each query was presented to ChatGPT, Gemini, and Claude using an identical patient-centred prompt. Responses (n=42) were anonymised and randomly ordered before being independently reviewed in a consensus meeting by a urology panel using the Quality Analysis of Medical Artificial Intelligence (QAMAI) framework. Comparative analysis used the Friedman test with Bonferroni-corrected pairwise Wilcoxon signed-rank testing. Results: Mean total QAMAI scores were 22.7 for ChatGPT (median, 23; range, 17 to 25), 22.6 for Claude (median, 23; range, 18 to 24), and 17.0 for Gemini (median, 17.5; range, 14 to 20), corresponding to moderate quality for ChatGPT and Claude and the boundary of poor and moderate quality for Gemini. The difference across models was significant (Friedman χ Conclusions: ChatGPT and Claude delivered broadly equivalent, moderate-to-good-quality information on patient-derived penile cancer questions, and both clearly outperformed Gemini, which frequently produced incomplete answers in the surgical and organ preservation domain. The universal absence of source citation is a clinically relevant limitation. These tools should be regarded as a supplement to, rather than a substitute for, specialist consultation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.