Evidence map›Paper›PMID 38635241›Full record

ArticleJAMA oncology2024

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer.

Jeffrey J Tosoian, Yuping Zhang, Lanbo Xiao, Cassie Xie, Nathan L Samora, Yashar S Niknafs, Zoey Chopra, Javed Siddiqui, Heng Zheng, Grace Herron and 19 more

Open access · hybridAbstract readValidation Study
In one paragraph

Article in JAMA oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
18.0field-weighted citation impact, top 1% of its field
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

47 citing papers in PubMed, 43 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. Leveraging Commercially Available Protein Assays as Biomarkers for Lung Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
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

29 authors at 9 institutions in 1 country.

Jeffrey J TosoianDepartment of Urology, Vanderbilt University Medical Center, Nashville, Tennessee.
Yuping ZhangDepartment of Pathology, University of Michigan, Ann Arbor.
Lanbo XiaoDepartment of Pathology, University of Michigan, Ann Arbor.
Cassie XieDepartment of Biostatistics, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Nathan L SamoraDepartment of Urology, Vanderbilt University Medical Center, Nashville, Tennessee.
Yashar S NiknafsDepartment of Pathology, University of Michigan, Ann Arbor.
Zoey ChopraDepartment of Pathology, University of Michigan, Ann Arbor.
Javed SiddiquiDepartment of Pathology, University of Michigan, Ann Arbor.
Heng ZhengDepartment of Pathology, University of Michigan, Ann Arbor.
Grace HerronDepartment of Pathology, University of Michigan, Ann Arbor.
Neil VaishampayanDepartment of Pathology, University of Michigan, Ann Arbor.
Hunter S RobinsonDepartment of Urology, Vanderbilt University Medical Center, Nashville, Tennessee.
Kumaran ArivoliDepartment of Pathology, University of Michigan, Ann Arbor.
Bruce J TrockDepartments of Pathology and Urology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Ashley E RossDepartment of Urology, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Todd M MorganDepartment of Urology, University of Michigan, Ann Arbor.
Ganesh S PalapattuDepartment of Urology, University of Michigan, Ann Arbor.
Simpa S SalamiDepartment of Urology, University of Michigan, Ann Arbor.
Lakshmi P KunjuDepartment of Pathology, University of Michigan, Ann Arbor.
Scott A TomlinsDepartment of Urology, University of Michigan, Ann Arbor.
Lori J SokollDepartments of Pathology and Urology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Daniel W ChanDepartments of Pathology and Urology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Sudhir SrivastavaDivision of Cancer Prevention, National Institutes of Health, Bethesda, Maryland.
Ziding FengDepartment of Biostatistics, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Martin G SandaDepartment of Urology, Emory University, Atlanta, Georgia.
Yingye ZhengDepartment of Biostatistics, Fred Hutchinson Cancer Research Center, Seattle, Washington.
John T WeiDepartment of Urology, University of Michigan, Ann Arbor.
Arul M ChinnaiyanDepartment of Pathology, University of Michigan, Ann Arbor.
EDRN-PCA3 Study Group
University of Michigan · USFred Hutch Cancer Center · USJohns Hopkins University · USVanderbilt University Medical Center · USEmory University · USHoward Hughes Medical Institute · USNational Institutes of Health · USNorthwestern University · USVanderbilt University · US

Funding

The Early Detection Research Network: Data Management and Coordinating CenterU24CA086368 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI RUTH D ETZIONI, Ziding Feng · 2010 to 2026
$75.7M
MICHIGAN MEDICAL SCIENTIST TRAINING PROGRAMT32GM007863 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI COLLINS, KATHLEEN L. · 1985 to 2024
$38.3M
Tissue/InformaticsP50CA186786 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Ganesh S Palapattu · 2014 to 2026
$27.6M
Prostate Cancer Biomarker and Imaging Validation Alliance: Emory University, University of Alabama Birmingham, and University of Texas SouthwesternU01CA113913 · NCI · EMORY UNIVERSITY · PI Martin G. Sanda · 2005 to 2026
$16.4M
Clinical and Analytical Validation of Cancer BiomarkersU24CA115102 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI · 2005 to 2021
$7.4M
Exploring Precision Oncology: From Gene Fusions to lncRNAsR35CA231996 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M · 2018 to 2024
$6.4M
Michigan-VUMC Biomarker Characterization CenterU2CCA271854 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ARUL M CHINNAIYAN · 2022 to 2026
$5.4M
Statistical Methods for Prospective Evaluation of BiomarkersR01CA236558 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI ZHENG, YINGYE · 2019 to 2024
$1.9M
Howard Hughes Medical InstituteNCI NIH HHS P50 CA186786NCI NIH HHS R01 CA236558NCI NIH HHS R35 CA231996NCI NIH HHS U01 CA113913NCI NIH HHS U24 CA086368NCI NIH HHS U24 CA115102NCI NIH HHS U2C CA271854NIGMS NIH HHS T32 GM007863
6 · The paper itself

Abstract

Importance: Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater). Objective: To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers. Design, Setting, and Participants: RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023. Exposure: Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy. Main Outcomes and Measures: Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily. Results: Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater. Conclusions and Relevance: In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

Indexed as

Biomarkers, TumorNeoplasm GradingProstatic NeoplasmsAgedEarly Detection of CancerHumansMaleMiddle AgedProstate-Specific AntigenBiomarkers, TumorProstate-Specific Antigen

Identifiers

PMID38635241
PMCPMC11190811
OpenAlexW4394914257

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.