{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T20:12:50Z","timestamp":1773173570222,"version":"3.50.1"},"reference-count":26,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T00:00:00Z","timestamp":1761177600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Prostate"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Prostate cancer (PCa) is the most common solid organ cancer in men and the fifth leading cause of cancer\u2010related deaths globally. PSA helps identify men at risk but has low specificity and has resulted in unnecessary biopsies. The PROSTest, a novel machine learning\u2010based 27\u2010gene mRNA liquid biopsy assay, was developed to detect PCa. We evaluated its utility as a stratification tool in symptomatic men undergoing biopsy or surgery for PSA\u2009&gt;\u20092\u2009ng\/mL.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Of 123 men assessed, 105 (85%) met eligibility criteria (age\u2009&gt;\u200955 years, PSA\u2009&gt;\u20092\u2009ng\/mL, symptomatic) and underwent image\u2010guided biopsy or surgery. Blood samples for PROSTest were collected prebiopsy, and RNA\u2010stabilized samples underwent RNA isolation and cDNA production. PCR results were analyzed using a machine learning algorithm, generating a 0\u2013100 score with a cutoff of 50 for a binary (positive\/negative) readout. The performance of PROSTest was against PSA using AUROC and evaluated for Gleason Grade (GG) 1 versus GG2\u20135 patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Median age was 68 years (55\u201386 years); median PSA was 8.2\u2009ng\/mL (IQR: 7.2\u201392\u2009ng\/mL). PCa was diagnosed in 65 men (62%) (27 GG1; 38 GG2\u20135). PROSTest was positive in 63\/65 (97%) of those with PCa and in 2\/40 (5%) without PCa. Sensitivity was 97%, specificity 96%. PROSTest outperformed PSA (AUROC: 0.99 vs. 0.61,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.0001). GG2\u20135 had significantly higher (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.0001) PROSTest scores (92\u2009\u00b1\u20093).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>PROSTest demonstrated superior sensitivity and specificity compared to PSA for detecting prostate cancer across all Gleason grades. Additionally, it showed potential for distinguishing GG2\u20135 from GG1\u2009+\u2009BPH, which could help guide clinical decision\u2010making and reduce unnecessary biopsies. By leveraging a machine learning\u2010based approach, PROSTest may offer a more accurate and less invasive diagnostic tool for prostate cancer stratification. However, larger prospective studies are needed to validate these findings and further define its clinical utility.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/pros.70086","type":"journal-article","created":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T17:19:33Z","timestamp":1761239973000},"page":"307-313","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Utility of the PROSTest, a Novel Blood\u2010Based Molecular Assay, Versus PSA for Prostate Cancer Stratification and Detection of Disease"],"prefix":"10.1002","volume":"86","author":[{"given":"Mark","family":"Kidd","sequence":"first","affiliation":[{"name":"Wren Laboratories Branford Connecticut USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Grzegorz","family":"Rempega","sequence":"additional","affiliation":[{"name":"Department of Urology Medical University of Silesia Katowice Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6390-1063","authenticated-orcid":false,"given":"Michal","family":"Kepinski","sequence":"additional","affiliation":[{"name":"Department of Urology Medical University of Silesia Katowice Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Szymon","family":"Slomian","sequence":"additional","affiliation":[{"name":"Department of Urology Regional Specialist Hospital No. 3 Rybnik Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krystyna","family":"Mlynarek","sequence":"additional","affiliation":[{"name":"Department of Urology Regional Specialist Hospital No. 3 Rybnik Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdel B.","family":"Halim","sequence":"additional","affiliation":[{"name":"Wren Laboratories Branford Connecticut USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,10,23]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.14740\/wjon1191"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2018.3710"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2024.03.027"},{"issue":"4","key":"e_1_2_12_5_1","first-page":"221","article-title":"The Use of Biomarkers in Prostate Cancer Screening and Treatment","volume":"19","author":"Alford A. 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