학술논문

Utility of PCA3 in patients undergoing repeat biopsy for prostate cancer
Document Type
article
Source
Prostate Cancer and Prostatic Diseases. 15(1)
Subject
Biomedical and Clinical Sciences
Clinical Sciences
Oncology and Carcinogenesis
Prevention
Aging
Urologic Diseases
Prostate Cancer
Cancer
Detection
screening and diagnosis
4.2 Evaluation of markers and technologies
Aged
Antigens
Neoplasm
Area Under Curve
Biomarkers
Tumor
Biopsy
Digital Rectal Examination
Humans
Male
Middle Aged
Multivariate Analysis
Prostate
Prostate-Specific Antigen
Prostatic Neoplasms
ROC Curve
Retrospective Studies
Ultrasonography
nomogram
decision curve analysis
prostate cancer antigen 3
repeat prostate biopsy
Urology & Nephrology
Clinical sciences
Oncology and carcinogenesis
Language
Abstract
BackgroundMen with persistently elevated and/or rising PSA levels after negative prostate biopsy often undergo multiple repeat biopsies. Prostate cancer antigen 3 (PCA3) has emerged as a predictor of prostate cancer.MethodsWe sought to define the utility of PCA3 in combination with other clinical data in predicting the risk of prostate cancer on repeat biopsy. We retrospectively obtained PCA3, PSA, PSA density (PSAD), digital rectal examination (DRE) and transrectal ultrasound (TRUS) findings from 103 patients at a single institution who had at least one prior negative prostate biopsy. The sensitivity and specificity of PCA3 in detecting prostate cancer was determined. Receiver operating characteristics curves were produced for each variable individually and in multivariable analysis, controlling for PCA3, PSAD, TRUS, PSA and DRE. A nomogram was created, internally validated and compared to another recently published nomogram.ResultsOf the 103 patients, 37 (31%) had prostate cancer on repeat biopsy. The sensitivity and specificity of PCA3 (using a cut point of 25) was 0.67 and 0.64, respectively. In multivariable analyses, PCA3 was independently associated with prostate cancer (odds ratio: 1.02, 95% confidence interval: 1.01-1.04), with area under the curve (AUC) of 0.64. A multivariable model containing PCA3, PSAD, PSA, DRE and TRUS findings showed the most diagnostic accuracy (AUC: 0.82).ConclusionsIn the setting of prior negative biopsies, PCA3 was independently associated with prostate cancer in a multivariable model. In combination with other clinical data, PCA3 is a valuable tool in assessing the risk of prostate cancer on repeat biopsy.