articleJAMA OncologyMar 31, 2016BRONZE OA

A Novel Urine Exosome Gene Expression Assay to Predict High-grade Prostate Cancer at Initial Biopsy

Columbia University · Icahn School of Medicine at Mount Sinai · +9 more institutions

PubMed
Indexed incrossrefpubmed

Abstract

Importance

Overdiagnosis and overtreatment of indolent prostate cancer (PCA) is a serious health issue in most developed countries. There is an unmet clinical need for noninvasive, easy to administer, diagnostic assays to help assess whether a prostate biopsy is warranted.

Objective

To determine the performance of a novel urine exosome gene expression assay (the ExoDx Prostate IntelliScore urine exosome assay) plus standard of care (SOC) (ie, prostate-specific antigen [PSA] level, age, race, and family history) vs SOC alone for discriminating between Gleason score (GS)7 and GS6 and benign disease on initial biopsy. DESIGN, SETTING, AND PARTICIPANTS: In training, using reverse-transcriptase polymerase chain reaction (PCR), we compared the urine exosome gene expression assay with biopsy outcomes in 499 patients with prostate-specific antigen (PSA) levels of 2 to 20 ng/mL. The derived prognostic score was then validated in 1064 patients from 22 community practice and academic urology clinic sites in the United States. Eligible participants included PCA-free men, 50 years or older, scheduled for an initial or repeated prostate needle biopsy due to suspicious digital rectal examination (DRE) findings and/or PSA levels (limit range, 2.0-20.0 ng/mL). MAIN OUTCOMES AND MEASURES: Evaluate the assay using the area under receiver operating characteristic curve (AUC) in discrimination of GS7 or greater from GS6 and benign disease on initial biopsy.

Citation impact

666
total citations
FWCI
41.39
Percentile
100%
References
65
Citations per year

Authors

14

Topics & keywords

Keywords
  • Medicine
  • Prostate cancer
  • Overdiagnosis
  • Biopsy
  • Prostate-specific antigen
  • Prostate biopsy
  • Rectal examination
  • PCA3
UN Sustainable Development Goals
  • Reduced inequalities
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