Evidence map›Paper›PMID 42299723›Full record

ArticleFuture oncology (London, England)2026

Development and validation of a digital pathology artificial intelligence (DPAI)-derived risk score predicting Gleason grade group reclassification for patients who are candidates for active surveillance.

Brent Mabey, Lauren H Lenz, Matthew J Schiewer, Walter Rayford, Hassan Muhammad, Wei Huang, Robert Finch, Christina Nakamoto, Hosein Kouros-Mehr, Jeff Jasper and 7 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Future oncology (London, England), 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
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0citing papers in PubMed
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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

17 authors.

Brent MabeyMyriad Genetics, Inc., Salt Lake City, UT, USA.
Lauren H LenzBiostatistics, Myriad Genetics, Inc., Salt Lake City, UT, USA.ORCID 0000-0003-1957-1068
Matthew J SchiewerClinical Research, Myriad Genetics, Inc., Salt Lake City, UT, USA.ORCID 0000-0002-2325-4228
Walter RayfordThe Urology Group, Memphis, TN, USA.
Hassan MuhammadPATHOMIQ, Inc., Cupertino, CA, USA.
Wei HuangPATHOMIQ, Inc., Cupertino, CA, USA.
Robert FinchMedical Affairs - Germline Oncology, Myriad Genetics, Inc., Salt Lake City, UT, USA.ORCID 0009-0004-7727-9748
Christina NakamotoMyriad Genetics, Inc., Salt Lake City, UT, USA.ORCID 0009-0001-0469-1676
Hosein Kouros-MehrMyriad Genetics, Inc., Salt Lake City, UT, USA.
Jeff JasperMyriad Genetics, Inc., Salt Lake City, UT, USA.
Hirak BasuPATHOMIQ, Inc., Cupertino, CA, USA.ORCID 0000-0001-7733-8008
Chao FengPATHOMIQ, Inc., Cupertino, CA, USA.
Anurag SharmaPATHOMIQ, Inc., Cupertino, CA, USA.
George WildingPATHOMIQ, Inc., Cupertino, CA, USA.ORCID 0009-0000-5775-5293
Rajat RoyPATHOMIQ, Inc., Cupertino, CA, USA.
Dale MuzzeyMyriad Genetics, Inc., Salt Lake City, UT, USA.ORCID 0000-0001-8822-2035
Alexander GutinMyriad Genetics, Inc., Salt Lake City, UT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsActive surveillance (AS) allows selected men with localized prostate cancer to defer curative therapy and reduce treatment morbidity. Conversion from AS to treatment is commonly triggered by Gleason grade group (GGG) upgrading on confirmatory biopsy. We developed and validated a digital pathology artificial intelligence (DPAI)-derived risk score to predict GGG upgrading in AS-eligible patients. MATERIALS AND

methodsThe DPAI model was trained using histopathology image features from diagnostic biopsies of 998 patients and validated in an independent cohort of 296 patients meeting criteria for AS. Logistic regression estimated the probability of confirmatory-biopsy GGG increase, and feature selection identified the most predictive variables.

resultsAI-GUR (Artificial Intelligence-Gleason Upgrade Risk) predicted GGG reclassification at confirmatory biopsy (OR 1.60;

conclusionsAI-GUR provides individualized estimates of confirmatory-biopsy GGG upgrading for AS candidates. Using DPAI may improve shared decision-making by complementing standard clinicopathologic tools and molecular testing using the same biopsy specimen, while informing the likelihood of grade upgrade at confirmation.

Indexed as

Artificial IntelligenceProstatic NeoplasmsWatchful WaitingAgedBiopsyHumansMaleMiddle AgedNeoplasm GradingProstateRisk Assessmentactive surveillancedigital pathology artificial intelligenceDPAI-derived risk scoregrade reclassificationProstate cancer

Identifiers

PMID42299723
PMCPMC13390508

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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.