Evidence map›Paper›PMID 39329071›Full record

ArticleEuropean urology open science2024

Effectiveness of the Medical Chatbot PROSCA to Inform Patients About Prostate Cancer: Results of a Randomized Controlled Trial.

Kilian Baumgärtner, Michael Byczkowski, Tamara Schmid, Marc Muschko, Philipp Woessner, Axel Gerlach, David Bonekamp, Heinz-Peter Schlemmer, Markus Hohenfellner, Magdalena Görtz

Abstract read
In one paragraph

Article in European urology open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  11. Artificial intelligence and patient education.Current opinion in urology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Kilian BaumgärtnerMedical Faculty, Ruprecht-Karls University of Heidelberg, Heidelberg, Germany.
Michael ByczkowskiSAP SE, Walldorf, Germany.
Tamara SchmidSAP SE, Walldorf, Germany.
Marc MuschkoSAP SE, Walldorf, Germany.
Philipp WoessnerSAP SE, Walldorf, Germany.
Axel GerlachSAP SE, Walldorf, Germany.
David BonekampDepartment of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Heinz-Peter SchlemmerDepartment of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Markus HohenfellnerDepartment of Urology, Heidelberg University Hospital, Heidelberg, Germany.
Magdalena GörtzDepartment of Urology, Heidelberg University Hospital, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objective: Artificial intelligence (AI)-powered conversational agents are increasingly finding application in health care, as these can provide patient education at any time. However, their effectiveness in medical settings remains largely unexplored. This study aimed to assess the impact of the chatbot "PROState cancer Conversational Agent" (PROSCA), which was trained to provide validated support from diagnostic tests to treatment options for men facing prostate cancer (PC) diagnosis. Methods: The chatbot PROSCA, developed by urologists at Heidelberg University Hospital and SAP SE, was evaluated through a randomized controlled trial (RCT). Patients were assigned to either the chatbot group, receiving additional access to PROSCA alongside standard information by urologists, or the control group (1:1), receiving standard information. A total of 112 men were included, of whom 103 gave feedback at study completion. Key findings and limitations: Over time, patients' information needs decreased significantly more in the chatbot group than in the control group ( Conclusions and clinical implications: With the introduction of the PROSCA chatbot, we created and evaluated an innovative, evidence-based AI health information tool as an additional source of information for PC. Our RCT results showed significant benefits of the chatbot in reducing patients' information needs and enhancing their understanding of PC. This easy-to-use AI tool provides accurate, timely, and accessible support, demonstrating its value in the PC diagnosis process. Future steps include further customization of the chatbot's responses and integration with the existing health care systems to maximize its impact on patient outcomes. Patient summary: This study evaluated an artificial intelligence-powered chatbot-PROSCA, a digital tool designed to support men facing prostate cancer diagnosis by providing validated information from diagnosis to treatment. Results showed that patients who used the chatbot as an additional tool felt better informed than those who received standard information from urologists. The majority of users appreciated the ease of use of the chatbot and expressed a desire to use it again; this suggests that PROSCA could be a valuable resource to improve patient understanding in prostate cancer diagnosis.

Indexed as

Artificial intelligenceChatbotEarly detectionLarge language modelNatural language processingProstate cancerRandomized controlled trial

Identifiers

PMID39329071
PMCPMC11424957

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.