Several studies have demonstrated the usefulness of monitoring an RNA transcript, such as PCA3, in post-prostate massage (PM) urine for increasing the specificity of prostate-specific antigen (PSA) in the detection of prostate cancer (PCa). However, a single marker may not necessarily reflect the multifactorial nature of PCa.
We analyzed post-PM urine samples from 154 consecutive patients, who presented for prostate biopsies because of elevated serum PSA (>4 ng/ml) and/or abnormal digital rectal exam. We tested whether the putative PCa biomarkers PSMA, PSGR, and PCA3 could be detected by quantitative real-time PCR in post-PM urine sediment. We combined these findings to test if a combination of these biomarkers could improve the specificity of actual diagnosis. Afterwards, we specifically tested our model for clinical usefulness in the PSA diagnostic “gray zone” (4–10 ng/ml) on a target subset of 82 men with no prior biopsy.
By univariate analysis, we found that the PSMA, PSGR, and PCA3 scores were significant predictors of PCa. Using a multiplex model, the area under the multi receiver-operating characteristic curve was 0.74 versus 0.82 in the diagnostic “gray zone.” Fixing the sensitivity at 96%, we obtained a specificity of 34% and 50% in the gray zone.
Taken together, these results provide a strategy for the development of a more accurate model for PCa diagnosis. In the future, a multiplexed, urine-based diagnostic test for PCa with a higher specificity, but the same sensitivity as the serum-PSA test, could be used to determine better which patients should undergo biopsy. Prostate 71:1736–1745, 2011. © 2011 Wiley Periodicals, Inc.