McNally Christopher J, Ruddock Mark W, Moore Tara, McKenna Declan J
Randox Laboratories Ltd, Crumlin, Co. Antrim BT29 4QY, Northern Ireland.
Biomedical Sciences Research Institute, Ulster University, Coleraine BT52 1SA, Northern Ireland.
Cancer Manag Res. 2020 Jul 1;12:5225-5241. doi: 10.2147/CMAR.S250829. eCollection 2020.
Prediction of prostate cancer in primary care is typically based upon serum total prostate-specific antigen (tPSA) and digital rectal examination results. However, these tests lack sensitivity and specificity, leading to over-diagnosis of disease and unnecessary, invasive biopsies. Therefore, there is a clinical need for diagnostic tests that can differentiate between benign conditions and early-stage malignant disease in the prostate. In this review, we evaluate research papers published from 2009 to 2019 reporting biomarkers that identified or differentiated benign prostatic hyperplasia (BPH) from prostate cancer. Our review identifies hundreds of potential biomarkers in urine, serum, tissue, and semen proposed as useful targets for differentiating between prostate cancer and BPH patients. However, it is still not apparent which of these candidate biomarkers are most useful, and many will not progress beyond the discovery stage unless they are properly validated for clinical practice. We conclude that this validation will come through the use of multivariate panels which can assess the value of biomarker candidates in combination with clinical parameters as part of a risk prediction calculator. Implementation of such a model will help clinicians stratify patients with prostate cancer symptoms in primary care, with tangible benefits for both the patient and the health service.
基层医疗中前列腺癌的预测通常基于血清总前列腺特异性抗原（tPSA）和直肠指检结果。然而，这些检查缺乏敏感性和特异性，导致疾病过度诊断以及不必要的侵入性活检。因此，临床上需要能够区分前列腺良性疾病和早期恶性疾病的诊断测试。在本综述中，我们评估了2009年至2019年发表的研究论文，这些论文报告了可识别或区分良性前列腺增生（BPH）与前列腺癌的生物标志物。我们的综述确定了尿液、血清、组织和精液中的数百种潜在生物标志物，这些标志物被提议作为区分前列腺癌患者和BPH患者的有用靶点。然而，目前尚不清楚这些候选生物标志物中哪些最为有用，而且许多生物标志物除非经过临床实践的适当验证，否则将无法超越发现阶段。我们得出结论，这种验证将通过使用多变量检测组合来实现，该组合可以结合临床参数评估候选生物标志物的价值，作为风险预测计算器的一部分。实施这样一个模型将有助于基层医疗中的临床医生对有前列腺癌症状的患者进行分层，对患者和医疗服务都有切实的好处。
