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A Predictive Model Based on Bi-parametric Magnetic Resonance Imaging and Clinical Parameters for Clinically Significant Prostate Cancer in the Korean Population

Authors
Noh, T.I.Hyun, C.W.Kang, H.E.Jin, H.J.Tae, J.H.Shim, J.S.Kang, S.G.Sung, D.J.Cheon, J.Lee, J.G.Kang, S.H.
Issue Date
10월-2021
Publisher
Korean Cancer Association
Keywords
Bi-parametric magnetic resonance imaging; Nomograms; Prostatic neoplasms; Transperineal prostate biopsy
Citation
Cancer Research and Treatment, v.53, no.4, pp.1148 - 1155
Indexed
SCIE
SCOPUS
KCI
Journal Title
Cancer Research and Treatment
Volume
53
Number
4
Start Page
1148
End Page
1155
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/139606
DOI
10.4143/crt.2020.1068
ISSN
1598-2998
Abstract
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] ≥ 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 ≥ 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. Copyright 2021by theKoreanCancerAssociation
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