Evidence map›Paper›PMID 42633351›Full record

ArticleCureus2026

Association of Histopathologic Characteristics in Diagnostic Prostate Biopsies With Decipher Genomic Classifier Risk Groups.

Selin Kurt, Ayesha Usman, Emily Torres, Garrison Pease

Abstract read
In one paragraph

Article in Cureus, 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

4 authors.

Selin KurtPathology, Albert Einstein College of Medicine, Montefiore Medical Center, New York City, USA.
Ayesha UsmanPathology, Albert Einstein College of Medicine, Montefiore Medical Center, New York City, USA.
Emily TorresPathology, Albert Einstein College of Medicine, Montefiore Medical Center, New York City, USA.
Garrison PeasePathology, Albert Einstein College of Medicine, Montefiore Medical Center, New York City, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer remains the most frequently diagnosed malignancy in men. While traditional clinicopathologic parameters guide management, genomic classifiers such as the Decipher assay are increasingly used to refine risk stratification. In this study, we evaluated the association between Decipher genomic classifier (GC) (GenomeDx Biosciences, Vancouver, BC, Canada) risk groups and histopathologic features in diagnostic prostate biopsy specimens within a routine clinical setting. We retrospectively reviewed 73 prostatic adenocarcinoma biopsies that underwent Decipher genomic testing, sampled between 2024 and 2025. Decipher risk groups demonstrated a significant association with grade groups (GG) (p=0.03 (χ²=16.6)), with high-risk (HR) cases showing a higher prevalence of higher GG compared to low-risk (LR) cases. Quantitative metrics of tumor burden were also significantly associated with risk groups: the mean positive core ratio (LR: 0.44 versus HR: 0.64; p=0.003) and mean maximum tumor length ratio (LR: 0.47 versus HR: 0.67; p=0.01) were significantly higher in the HR group. Aggressive features such as extraprostatic extension and intraductal carcinoma were identified exclusively in the HR group. No significant differences were observed for prostate-specific antigen (PSA) levels across groups. In conclusion, histopathologic indicators of tumor aggressiveness and burden in diagnostic prostate biopsies show significant association with Decipher GC risk groups, supporting their complementary role in risk stratification.

Indexed as

decipher genomic classifierprostate adenocarcinomaprostate biopsyprostate cancerrisk stratification

Identifiers

PMID42633351
PMCPMC13499612

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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.