Research Unit in Biomedicine and Translational and Pediatric Oncology, Vall d'Hebron Research Institute, Barcelona, Spain.
Prostate. 2011 Dec;71(16):1736-45. doi: 10.1002/pros.21390. Epub 2011 Apr 25.
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.
多项研究已经证实，在前列腺按摩后（PM）尿液中监测 RNA 转录物（如 PCA3）有助于提高前列腺特异性抗原（PSA）检测前列腺癌（PCa）的特异性。然而，单一标志物不一定能反映 PCa 的多因素性质。
我们分析了 154 例连续因血清 PSA（>4ng/ml）升高和/或直肠指检异常而接受前列腺活检的患者的 PM 后尿液样本。我们通过定量实时 PCR 检测 PM 尿沉渣中是否可检测到假定的 PCa 标志物 PSMA、PSGR 和 PCA3。我们将这些发现结合起来，以检验这些生物标志物的组合是否可以提高实际诊断的特异性。然后，我们在一个没有先前活检的 82 名男性的目标子集中专门测试了我们模型在 PSA 诊断“灰色区域”（4-10ng/ml）的临床实用性。
通过单变量分析，我们发现 PSMA、PSGR 和 PCA3 评分是 PCa 的显著预测因子。使用多重模型，在诊断“灰色区域”中，多接收器工作特征曲线下的面积为 0.74 对 0.82。在固定敏感性为 96%的情况下，我们在灰色区域获得了 34%和 50%的特异性。
总的来说，这些结果为开发更准确的 PCa 诊断模型提供了一种策略。未来，一种基于尿液的多重诊断测试，其特异性高于血清 PSA 测试，但敏感性相同，可用于更好地确定哪些患者应进行活检。
