Mosaiques diagnostics GmbH, Hannover, Germany.
Urology Department, Reina Sofía University Hospital, Cordoba, Spain.
Br J Cancer. 2019 Jun;120(12):1120-1128. doi: 10.1038/s41416-019-0472-z. Epub 2019 May 16.
Prostate cancer progresses slowly when present in low risk forms but can be lethal when it progresses to metastatic disease. A non-invasive test that can detect significant prostate cancer is needed to guide patient management.
Capillary electrophoresis/mass spectrometry has been employed to identify urinary peptides that may accurately detect significant prostate cancer. Urine samples from 823 patients with PSA (<15 ng/ml) were collected prior to biopsy. A case-control comparison was performed in a training set of 543 patients (n = 98; n = 445) and a validation set of 280 patients (n = 48, n = 232). Totally, 19 significant peptides were subsequently combined by a support vector machine algorithm.
Independent validation of the 19-biomarker model in 280 patients resulted in a 90% sensitivity and 59% specificity, with an AUC of 0.81, outperforming PSA (AUC = 0.58) and the ERSPC-3/4 risk calculator (AUC = 0.69) in the validation set.
This multi-parametric model holds promise to improve the current diagnosis of significant prostate cancer. This test as a guide to biopsy could help to decrease the number of biopsies and guide intervention. Nevertheless, further prospective validation in an external clinical cohort is required to assess the exact performance characteristics.
前列腺癌在低危形式下进展缓慢，但当进展为转移性疾病时可能致命。需要一种非侵入性的测试，可以检测到显著的前列腺癌，以指导患者管理。
采用毛细管电泳/质谱法鉴定可能准确检测显著前列腺癌的尿肽。在活检前收集了 823 名 PSA（<15ng/ml）患者的尿液样本。在训练集 543 例患者（n=98；n=445）和验证集 280 例患者（n=48，n=232）中进行了病例对照比较。随后，通过支持向量机算法对 19 个显著肽进行了组合。
在 280 例患者中对 19 种生物标志物模型的独立验证结果为 90%的敏感性和 59%的特异性，AUC 为 0.81，优于 PSA（AUC=0.58）和 ERSPC-3/4 风险计算器（AUC=0.69）在验证集中。
该多参数模型有望改善目前对显著前列腺癌的诊断。这种作为活检指南的检测方法可以帮助减少活检数量并指导干预。然而，需要在外部临床队列中进行进一步的前瞻性验证，以评估其确切的性能特征。
