BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Lourdes Mengual; Juan José Lozano; Mercedes Ingelmo-Torres; Laura Izquierdo; Mireia Musquera; María José Ribal; Antonio Alcaraz Journal: BMC Cancer Date: 2016-02-09 Impact factor: 4.430
Authors: Marina Rigau; Mireia Olivan; Marta Garcia; Tamara Sequeiros; Melania Montes; Eva Colás; Marta Llauradó; Jacques Planas; Inés de Torres; Juan Morote; Colin Cooper; Jaume Reventós; Jeremy Clark; Andreas Doll Journal: Int J Mol Sci Date: 2013-06-17 Impact factor: 5.923