{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T20:16:43Z","timestamp":1783023403653,"version":"3.54.6"},"reference-count":18,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T00:00:00Z","timestamp":1775260800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T00:00:00Z","timestamp":1775260800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Laboratory Analysis"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Prebiopsy multiparametric MRI (mpMRI) reported using the Prostate Imaging Reporting and Data System (PI\u2010RADS) improves prostate cancer triage, yet false\u2010positive findings remain common and may drive unnecessary biopsy. Prostate\u2010specific antigen density (PSAD) is an inexpensive laboratory\u2010derived adjunct that may refine MRI\u2010based risk stratification.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrospectively screened 713 transrectal ultrasound (TRUS)\u2010guided biopsy episodes from a single experienced urologist's practice at a tertiary referral hospital between October 2022 and August 2025 and included 375 men with prebiopsy mpMRI reported using PI\u2010RADS version 2.1 and complete data for prespecified predictors. All patients underwent systematic 12\u2010core TRUS\u2010guided biopsy. Clinically significant prostate cancer (csPCa) was defined as International Society of Urological Pathology (ISUP) grade group \u2265\u20092. We developed logistic regression models combining PSAD and PI\u2010RADS (parsimonious model) and adding age and digital rectal examination (DRE) (full model). Discrimination (AUC), calibration, and clinical utility (decision curve analysis) were assessed, and the incremental value of PSAD beyond PI\u2010RADS for csPCa was quantified using IDI and continuous NRI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      csPCa was present in 93\/375 (24.8%) and any prostate cancer in 144\/375 (38.4%). For csPCa prediction, AUC was 0.746 for PI\u2010RADS and 0.760 for PSAD; the combined PSAD+PI\u2010RADS model achieved AUC 0.798 and the full model AUC 0.794. Adding PSAD to PI\u2010RADS improved IDI (0.0528;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) and total continuous NRI (0.3926;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), driven mainly by improved down\u2010classification of non\u2010csPCa cases.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Integrating PSAD with PI\u2010RADS improved csPCa risk stratification compared with PI\u2010RADS alone, with predominant benefit as a biopsy\u2010sparing, rule\u2010out adjunct. External validation is required for clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcla.70218","type":"journal-article","created":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T08:05:33Z","timestamp":1775289933000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating Prostate\u2010Specific Antigen Density and Prostate Imaging Reporting and Data System Scores to Optimize Detection of Clinically Significant Prostate Cancer: A Multivariable Risk Model Approach"],"prefix":"10.1002","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7836-0490","authenticated-orcid":false,"given":"Yunus","family":"Kayali","sequence":"first","affiliation":[{"name":"Department of Urology University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital  Istanbul Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,4]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2018.3710"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2019.02.033"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140\u20106736(16)32401\u20101"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1801993"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020190646"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2024.03.027"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2021.07.024"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1111\/bju.15277"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.juro.2017.03.130"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.urolonc.2022.08.003"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41391\u2010022\u201000549\u2010y"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euo.2018.09.001"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0b013e3181c30fb2"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2017.12126"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1177\/0272989X06295361"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2929"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13111939"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1097\/CU9.0000000000000173"}],"container-title":["Journal of Clinical Laboratory Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jcla.70218","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/jcla.70218","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jcla.70218","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T19:22:49Z","timestamp":1783020169000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jcla.70218"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,4]]},"references-count":18,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["10.1002\/jcla.70218"],"URL":"https:\/\/doi.org\/10.1002\/jcla.70218","archive":["Portico"],"relation":{},"ISSN":["0887-8013","1098-2825"],"issn-type":[{"value":"0887-8013","type":"print"},{"value":"1098-2825","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,4]]},"assertion":[{"value":"2025-12-04","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-03-23","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70218"}}