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.
European urology oncology. 2021 Aug 04 [Epub ahead of print]
Hendrik Van Poppel, Renée Hogenhout, Peter Albers, Roderick C N van den Bergh, Jelle O Barentsz, Monique J Roobol
Department of Development and Regeneration, University Hospital KU Leuven, Leuven, Belgium. Electronic address: ., Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands., Department of Urology, Heinrich-Heine University Medical Faculty, Düsseldorf, Germany; Division of Personalized Early Detection of Prostate Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany., Department of Urology, St. Antonius Hospital, Utrecht, The Netherlands., Department of Medical Imaging, Radboudumc, Nijmegen, The Netherlands.