ArticleBMC urology2024
Performance of large language models (LLMs) in providing prostate cancer information.
Article in BMC urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07489261 (Effect of Mobile Application- and Artificial Intelligence-Supported Video-Based Patient Education on Patient Outcomes in Teaching Clean Intermittent Catheterization), which is not on this map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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.
Effect of Mobile Application- and Artificial Intelligence-Supported Video-Based Patient Education on Patient Outcomes in Teaching Clean Intermittent Catheterization
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparison of the readability of ChatGPT and Bard in medical communication: a meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Integrating large language models into prostate cancer training: evidence from comparative benchmarking and a pilot randomized trial.BMC medical education · 2026Trial
- Evaluating the impact of AI-generated educational content on patient understanding and anxiety in endodontics and restorative dentistry: a comparative study.BMC oral health · 2025Trial
- Quality and Readability Analysis of Artificial Intelligence-Generated Medical Information Related to Prostate Cancer: A Cross-Sectional Study of ChatGPT and DeepSeek.The world journal of men's health · 2026Article
- Article
- Quality and Usability of Prostate Cancer Information Generated by Artificial Intelligence Chatbots: A Comparative Analysis.Cancers · 2026Article
- Generative AI for patient education in cancer care: A scoping review of evaluation practices and emerging trends.Technical innovations & patient support in radiation oncology · 2026Review
- Multimodal artificial intelligence in urologic precision oncology: from algorithm to translational medicine (a systemized narrative review).Frontiers in oncology · 2026Review
- Assessing the Accuracy of ChatGPT's Answers to Basic Questions on Uterine and Cervical Cancers.Oman medical journal · 2026Article
- Article
- Automated Extraction of Imaging and Pathology Data From Diverse Prostate Cancer Electronic Records.JCO clinical cancer informatics · 2025Article
- Comparative analysis of the performance of the large language models DeepSeek-V3, DeepSeek-R1, open AI-O3 mini and open AI-O3 mini high in urology.World journal of urology · 2025Article
- Evaluating an AI Chatbot "Prostate Cancer Info" for Providing Quality Prostate Cancer Screening Information: Cross-Sectional Study.JMIR cancer · 2025Article
- Artificial intelligence and patient education.Current opinion in urology · 2025Review
- An overview of utilizing artificial intelligence in localized prostate cancer imaging.Expert review of medical devices · 2025Review
- ChatGPT's competence in responding to urological emergencies.Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES · 2025Article
- Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025Article
- Evaluating the Feasibility of ChatGPT-4 as a Knowledge Resource in Bariatric Surgery: A Preliminary Assessment.Obesity surgery · 2025Article
- Exploring Large Language Models and the Metaverse for Urologic Applications: Potential, Challenges, and the Path Forward.International neurourology journal · 2024Article
- The Potential Impact of Large Language Models on Doctor-Patient Communication: A Case Study in Prostate Cancer.Healthcare (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe diagnosis and management of prostate cancer (PCa), the second most common cancer in men worldwide, are highly complex. Hence, patients often seek knowledge through additional resources, including AI chatbots such as ChatGPT and Google Bard. This study aimed to evaluate the performance of LLMs in providing education on PCa.
methodsCommon patient questions about PCa were collected from reliable educational websites and evaluated for accuracy, comprehensiveness, readability, and stability by two independent board-certified urologists, with a third resolving discrepancy. Accuracy was measured on a 3-point scale, comprehensiveness was measured on a 5-point Likert scale, and readability was measured using the Flesch Reading Ease (FRE) score and Flesch-Kincaid FK Grade Level.
resultsA total of 52 questions on general knowledge, diagnosis, treatment, and prevention of PCa were provided to three LLMs. Although there was no significant difference in the overall accuracy of LLMs, ChatGPT-3.5 demonstrated superiority over the other LLMs in terms of general knowledge of PCa (p = 0.018). ChatGPT-4 achieved greater overall comprehensiveness than ChatGPT-3.5 and Bard (p = 0.028). For readability, Bard generated simpler sentences with the highest FRE score (54.7, p < 0.001) and lowest FK reading level (10.2, p < 0.001).
conclusionChatGPT-3.5, ChatGPT-4 and Bard generate accurate, comprehensive, and easily readable PCa material. These AI models might not replace healthcare professionals but can assist in patient education and guidance.
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.