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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
A Predictive Model Based on Bi-parametric Magnetic Resonance Imaging and Clinical Parameters for Clinically Significant Prostate Cancer in the Korean Population
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한암학회 Cancer Research and Treatment Cancer Research and Treatment 제53권 제4호 KCI Accredited Journals
- 발행연도
- 2021.10
- 수록면
- 1,148 - 1,155 (8page)
- DOI
- 10.4143/crt.2020.1068
이용수
A Predictive Model Based on Bi-parametric Magnetic Resonance Imaging and Clinical Parameters for Clinically Significant Prostate Cancer in the Korean Population
초록· 키워드
오류제보하기
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.
목차
등록된 정보가 없습니다.
참고문헌 (28)
참고문헌 신청
Zhu X / 2012 / Risk-based prostate cancer screening / Eur Urol 61:652~661
Roobol MJ / 2010 / A risk-based strategy improves prostate-specific antigen-driven detection of prostate cancer / Eur Urol 57:79~85
Mehralivand S / 2018 / A magnetic resonance imaging-based prediction model for prostate biopsy risk stratification / JAMA Oncol 4:678~685
Palsdottir T / 2019 / A unified prostate cancer risk prediction model combining the Stockholm3 test and magnetic resonance imaging / Eur Urol Oncol 2:490~496
Cucchiara V / 2018 / Genomic markers in prostate cancer decision making / Eur Urol 73:572~582
Roobol MJ / 2010 / A risk-based strategy improves prostate-specific antigen-driven detection of prostate cancer / Eur Urol 57:79~85
Mehralivand S / 2018 / A magnetic resonance imaging-based prediction model for prostate biopsy risk stratification / JAMA Oncol 4:678~685
Palsdottir T / 2019 / A unified prostate cancer risk prediction model combining the Stockholm3 test and magnetic resonance imaging / Eur Urol Oncol 2:490~496
Cucchiara V / 2018 / Genomic markers in prostate cancer decision making / Eur Urol 73:572~582
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