{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:00:50Z","timestamp":1764842450398},"reference-count":28,"publisher":"Korean Cancer Association","issue":"4","license":[{"start":{"date-parts":[[2020,12,31]],"date-time":"2020-12-31T00:00:00Z","timestamp":1609372800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006468","name":"College of Medicine, Korea University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006468","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["e-crt.org"],"crossmark-restriction":true},"short-container-title":["Cancer Res Treat"],"published-print":{"date-parts":[[2021,10,15]]},"abstract":"<jats:p>Purpose This study aimed to develop and validate a predictive model for the assessment of clinically significant prostate cancer (csPCa) in men, prior to prostate biopsies, based on bi-parametric magnetic resonance imaging (bpMRI) and clinical parameters.Materials and Methods We retrospectively analyzed 300 men with clinical suspicion of prostate cancer (prostate-specific antigen [PSA] \u2265 4.0 ng\/mL and\/or abnormal findings in a digital rectal examination), who underwent bpMRI-ultrasound fusion transperineal targeted and systematic biopsies in the same session, at a Korean university hospital. Predictive models, based on Prostate Imaging Reporting and Data Systems scores of bpMRI and clinical parameters, were developed to detect csPCa (intermediate\/high grade [Gleason score \u2265 3+4]) and compared by analyzing the areas under the curves and decision curves.Results A predictive model defined by the combination of bpMRI and clinical parameters (age, PSA density) showed high discriminatory power (area under the curve, 0.861) and resulted in a significant net benefit on decision curve analysis. Applying a probability threshold of 7.5%, 21.6% of men could avoid unnecessary prostate biopsy, while only 1.0% of significant prostate cancers were missed.Conclusion This predictive model provided a reliable and measurable means of risk stratification of csPCa, with high discriminatory power and great net benefit. It could be a useful tool for clinical decision-making prior to prostate biopsies.<\/jats:p>","DOI":"10.4143\/crt.2020.1068","type":"journal-article","created":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T22:55:02Z","timestamp":1610319302000},"page":"1148-1155","update-policy":"http:\/\/dx.doi.org\/10.4143\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Predictive Model Based on Bi-parametric Magnetic Resonance Imaging and Clinical Parameters for Clinically Significant Prostate Cancer in the Korean Population"],"prefix":"10.4143","volume":"53","author":[{"given":"Tae Il","family":"Noh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang Wan","family":"Hyun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ha Eun","family":"Kang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyun 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