Evidence map›Paper›PMID 42775044›Full record

ArticleBJUI compass2026

Lower trust in artificial intelligence than physicians coexists with high willingness to engage in artificial intelligence-assisted prostate cancer management among active surveillance patients.

Eric S Chai, Kaitlynn Abraham, Riley Hanes, Adam Williams, Howard Wolinsky, Oleksandr N Kryvenko, Radka Stoyanova, Frank J Penedo, Archan Khandekar, Bruno Nahar and 3 more

Abstract read
In one paragraph

Article in BJUI compass, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Eric S ChaiSchool of Medicine University of Missouri-Kansas City Kansas City Missouri USA.ORCID https://orcid.org/0009-0001-6089-3811
Kaitlynn AbrahamDr. Kiran C. Patel College of Osteopathic Medicine Nova Southeastern University Davie Florida USA.
Riley HanesBrady Urology Institute Johns Hopkins School of Medicine Baltimore Maryland USA.
Adam WilliamsMiller School of Medicine University of Miami Miami Florida USA.
Howard WolinskyFreelance Medical Journalist at "The Active Surveillor" USA.ORCID https://orcid.org/0000-0003-4426-6735
Oleksandr N KryvenkoDepartment of Pathology and Laboratory Medicine University of Miami Miller School of Medicine Miami Florida USA.
Radka StoyanovaDepartment of Radiation Oncology University of Miami Miller School of Medicine Miami Florida USA.
Frank J PenedoSylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami Florida USA.
Archan KhandekarSylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami Florida USA.ORCID https://orcid.org/0000-0003-3177-3439
Bruno NaharSylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami Florida USA.
Mark L GonzalgoSylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami Florida USA.
Dipen J ParekhSylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami Florida USA.
Sanoj PunnenSylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami Florida USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to examine the sentiment for artificial intelligence (AI) among prostate cancer (PCa) patients on active surveillance (AS) and to evaluate how that sentiment relates to patient willingness to engage with AI. Materials and Methods: We conducted a 23-question online survey (November-December 2025) distributed through an AS platform. Analyses were restricted to 110 respondents with PCa on AS. Outcomes included trust ratings (10-point Likert scale) for physicians versus AI, responses to hypothetical AI management recommendations and perceived concerns and facilitators of trust. Statistical analyses included the Wilcoxon signed-rank tests, the McNemar tests and Fisher's exact tests. Results: Median trust in urologists (8 [IQR 7-9]) exceeded that for AI (6 [IQR 5-7]), with smaller differences for radiologists and pathologists compared with diagnostic AI (all Conclusions: Among AS patients, lower trust in AI compared to physicians coexists with a high optimism for AI and willingness to incorporate AI recommendations into decision-making. This discordance suggests that behavioural adoption of AI-assisted care may precede full patient confidence.

Indexed as

active surveillanceartificial intelligenceprostate cancertreatmenttrust

Identifiers

PMID42775044
PMCPMC13595033

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.