Detection of prostate cancer using prostate imaging reporting and data system score and prostate-specific antigen density in biopsy-naive and prior biopsy-negative patients

Few studies report on indications for prostate biopsy using Prostate Imaging–Reporting and Data System (PI-RADS) score and prostate-specific antigen density (PSAD). No study to date has included biopsy-naïve and prior biopsy-negative patients. Therefore, we evaluated the predictive values of the PI-...

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Veröffentlicht in:Prostate international 2020-09, Vol.8 (3), p.125-129
Hauptverfasser: Ryoo, Hyunsoo, Kang, Min Yong, Sung, Hyun Hwan, Chang Jeong, Byong, Seo, Seong Il, Jeon, Seong Soo, Lee, Hyun Moo, Jeon, Hwang Gyun
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Sprache:eng
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Zusammenfassung:Few studies report on indications for prostate biopsy using Prostate Imaging–Reporting and Data System (PI-RADS) score and prostate-specific antigen density (PSAD). No study to date has included biopsy-naïve and prior biopsy-negative patients. Therefore, we evaluated the predictive values of the PI-RADS, version 2 (v2) score combined with PSAD to decrease unnecessary biopsies in biopsy-naïve and prior biopsy-negative patients. A total of 1,098 patients who underwent multiparametric magnetic resonance imaging at our hospital before a prostate biopsy and who underwent their second prostate biopsy with an initial benign negative prostatic biopsy were included. We found factors associated with clinically significant prostate cancer (csPca). We assessed negative predictive values by stratifying biopsy outcomes by prior biopsy history and PI-RADS score combined with PSAD. The median age was 65 years (interquartile range: 59-70), and the median PSA was 5.1 ng/mL (interquartile range: 3.8-7.1). Multivariate logistic regression analysis revealed that age, prostate volume, PSAD, and PI-RADS score were independent predictors of csPca. In a biopsy-naïve group, 4% with PI-RADS score 1 or 2 had csPca; in a prior biopsy-negative group, 3% with PI-RADS score 1 or 2 had csPca. The csPca detection rate was 2.0% for PSA density
ISSN:2287-8882
2287-903X
DOI:10.1016/j.prnil.2020.03.003