Evidence map›Paper›PMID 42279322›Full record

ArticleCancers2026

Study of Bladder Cancer Detection in Standard White Light Versus AI-Supported Endoscopy-02 (RAISE-02)-A Randomized Controlled Non-Inferiority Trial.

Peter Blak Hjort, Katharina Skovhus, Jørgen Bjerggaard Jensen, Andreas Ernst

Abstract read
In one paragraph

Article in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Peter Blak HjortDepartment of Clinical Medicine, Aarhus University, Palle Juul-Jensens Blvd. 82, 8200 Aarhus N, Denmark.ORCID 0000-0002-3931-9727
Katharina SkovhusDepartment of Clinical Medicine, Aarhus University, Palle Juul-Jensens Blvd. 82, 8200 Aarhus N, Denmark.ORCID 0009-0003-4112-1626
Jørgen Bjerggaard JensenDepartment of Clinical Medicine, Aarhus University, Palle Juul-Jensens Blvd. 82, 8200 Aarhus N, Denmark.ORCID 0000-0002-4347-739X
Andreas ErnstDepartment of Clinical Medicine, Aarhus University, Palle Juul-Jensens Blvd. 82, 8200 Aarhus N, Denmark.

Funding

Cystotech ApS 2024-731-24979 K16
6 · The paper itself

Abstract

backgroundWhite light cystoscopy (WLC) is the gold standard for bladder cancer (BC) detection and surveillance, but has limited sensitivity, particularly for small and flat lesions. We evaluated the diagnostic performance and safety of a real-time artificial intelligence (AI)-assisted support tool (CystoAID©) for bladder cancer detection.

methodsThis single-center, randomized, controlled non-inferiority trial included 64 patients undergoing transurethral resection of bladder tumor or laser fulguration for suspected primary or recurrent BC. Patients were randomized 1:1 to WLC alone or WLC followed by AI-assisted cystoscopy. The primary outcome was per-lesion sensitivity of CystoAID vs. WLC within the intervention group. The reference standard was histopathology or clinical evaluation. The predefined non-inferiority margin was -5%. Secondary outcomes included sensitivity for lesions ≤ 5 mm, false positives, procedural duration, and safety (30-day adverse events).

resultsA total of 142 lesions were identified (84 intervention, 58 control). Sensitivity was 96.2% (95% CI 87.0-99.5) for CystoAID and 88.7% (95% CI 77.0-95.7) for WLC (difference 7.5%; 95% CI -2.7 to 17.8), demonstrating non-inferiority. In a sub-analysis for lesions ≤ 5 mm (

conclusionsCystoAID demonstrated non-inferior sensitivity to WLC and could be safely integrated into the routine clinical workflow. Larger studies with improved representation of flat lesions are warranted, as well as to assess whether CystoAID can achieve superior sensitivity compared with standard WLC.

Indexed as

artificial intelligencebladder cancerdetectiondiagnosissensitivity

Identifiers

PMID42279322
PMCPMC13255740

What OpenQuestion holds

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LicenceCC BY
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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.