Department of Urology, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Mol Diagn Ther. 2013 Feb;17(1):1-8. doi: 10.1007/s40291-013-0014-y.
Prostate cancer (PCa) screening and detection have changed dramatically since the introduction of serum prostate-specific antigen (PSA) testing. Despite the resulting improvement in early PCa detection and stage migration, in clinical practice the use of PSA testing may cause overdetection and ultimately overtreatment. As a consequence, novel biomarkers are needed to increase the specificity of PCa detection. The aim of this article is to present an overview of novel blood- and urine-based biomarkers that may optimize PCa detection, with improved identification of patients with significant PCa and avoidance of unnecessary prostate biopsies. A systematic and comprehensive PubMed search was performed using the MeSH search terms 'prostate cancer', 'biomarker', 'marker', and 'detection'. Results were restricted to the English language. Several blood- and urine-based biomarkers have the potential to improve prediction of the presence and/or significance of PCa. Ideally, biomarkers should be used in combination within multivariate models, leading to superior accuracy for prediction of any PCa or clinically significant PCa, compared with the use of a single marker.
前列腺癌（PCa）筛查和检测自引入血清前列腺特异性抗原（PSA）检测以来发生了巨大变化。尽管早期 PCa 的检测和分期迁移有所改善，但在临床实践中，PSA 检测的使用可能导致过度检测，并最终导致过度治疗。因此，需要新的生物标志物来提高 PCa 检测的特异性。本文旨在介绍新型的基于血液和尿液的生物标志物，这些标志物可能优化 PCa 的检测，更好地识别有显著 PCa 的患者，并避免不必要的前列腺活检。使用 MeSH 搜索词“前列腺癌”、“生物标志物”、“标志物”和“检测”，对 PubMed 进行了系统和全面的搜索。结果仅限于英文。一些基于血液和尿液的生物标志物具有改善 PCa 存在和/或意义的预测能力。理想情况下，生物标志物应在多变量模型中联合使用，与使用单个标志物相比，对任何 PCa 或临床显著 PCa 的预测具有更高的准确性。
