Department of Development and Regeneration, University Hospital KU Leuven, Leuven, Belgium.
Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Eur Urol Oncol. 2021 Oct;4(5):731-739. doi: 10.1016/j.euo.2021.06.006. Epub 2021 Aug 4.
Overdiagnosis as the argument to stop prostate cancer (PCa) screening is less valid since the introduction of new technologies such as risk calculators (RCs) and magnetic resonance imaging (MRI). These new technologies result in fewer unnecessary biopsy procedures and fewer cases of both overdiagnosis and underdetection. Therefore, we can now adequately respond to the growing and urgent need for a structured risk assessment to detect PCa early.
To provide expert discussion on the existing evidence for a previously published risk-stratified strategy regarding an organised population-based early detection programme for PCa.
The proposed algorithm for early detection of PCa emerged from expert consensus by the authors based on available evidence derived from a nonsystematic review of the current literature using Medline/PubMed, Cochrane Library database, ClinicalTrials.gov, ISRCTN Registry, and the European Association of Urology guidelines on PCa.
Although not confirmed by the highest level of evidence, current literature and guidelines point towards an algorithm for early detection of PCa that starts with risk-based prostate-specific antigen (PSA) testing, followed by multivariable risk stratification with RCs. All men who are classified to be at intermediate and high risk are then offered prostate MRI. The combined data from RCs and MRI results can be used to select men for prostate biopsy. Low-risk men return to a risk-based safety net that includes individualised PSA-interval tests and, if necessary, repeated MRI. Depending on local availability, the use of the different risk stratification tools may be adapted.
We present a risk-stratified algorithm for an organised population-based early detection programme for clinically significant PCa. Although the proposed strategy has not yet been analysed prospectively, it exploits and may even improve the most important available benefits of "PSA-only" screening studies, while at the same time reduces unnecessary biopsies and overdiagnosis by using new risk stratification tools.
This paper presents a personalised strategy that enables selective early detection of prostate cancer by combining prostate-specific antigen (interval) testing' prediction models (risk calculators), and magnetic resonance imaging scans. This will likely lead to reduced prostate cancer-related morbidity and mortality, while reducing the need for prostate biopsy and limiting overdiagnosis.
随着新型技术(如风险计算器和磁共振成像)的引入,过度诊断作为停止前列腺癌(PCa)筛查的论点已不成立。这些新技术可减少不必要的活检程序,并减少过度诊断和漏诊的病例。因此,我们现在可以充分应对不断增长的早期发现 PCa 的结构化风险评估的迫切需求。
提供关于之前发表的风险分层策略的现有证据的专家讨论,该策略涉及针对 PCa 的有组织的基于人群的早期检测计划。
作者基于现有证据,通过专家共识提出了 PCa 的早期检测算法,这些证据来自对当前文献的非系统性综述,使用了 Medline/PubMed、Cochrane 图书馆数据库、ClinicalTrials.gov、ISRCTN 注册中心和欧洲泌尿外科协会关于 PCa 的指南。
尽管没有最高级别的证据证实,但当前文献和指南都指出了一种用于 PCa 早期检测的算法,该算法从基于风险的前列腺特异性抗原(PSA)测试开始,然后通过风险计算器进行多变量风险分层。所有被归类为中高风险的男性随后都接受前列腺 MRI 检查。RC 和 MRI 结果的综合数据可用于选择进行前列腺活检的男性。低风险男性返回基于风险的安全网,包括个体化 PSA 间隔测试,如果必要,重复 MRI。根据当地的可用性,可以调整使用不同的风险分层工具。
我们提出了一种针对有组织的基于人群的早期检测计划的风险分层算法,用于检测有临床意义的 PCa。尽管该策略尚未进行前瞻性分析,但它利用了“仅 PSA”筛查研究的最重要的可用益处,甚至可能加以改进,同时通过使用新的风险分层工具减少不必要的活检和过度诊断。
本文提出了一种个性化策略,通过结合前列腺特异性抗原(间隔)测试预测模型(风险计算器)和磁共振成像扫描来选择性地早期发现前列腺癌。这可能会降低前列腺癌相关发病率和死亡率,同时减少前列腺活检的需求,并限制过度诊断。