Literature DB >> 34364829

A European Model for an Organised Risk-stratified Early Detection Programme for Prostate Cancer.

Hendrik Van Poppel1, Renée Hogenhout2, Peter Albers3, Roderick C N van den Bergh4, Jelle O Barentsz5, Monique J Roobol2.   

Abstract

CONTEXT: 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.
OBJECTIVE: 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. EVIDENCE ACQUISITION: 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. EVIDENCE SYNTHESIS: 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.
CONCLUSIONS: 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. PATIENT
SUMMARY: 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.
Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Active surveillance; Early detection; Magnetic resonance imaging; Prostate Imaging Reporting and Data System; Prostate cancer; Risk calculator; Risk stratification; Screening

Mesh:

Substances:

Year:  2021        PMID: 34364829     DOI: 10.1016/j.euo.2021.06.006

Source DB:  PubMed          Journal:  Eur Urol Oncol        ISSN: 2588-9311


  10 in total

1.  External validation of the Rotterdam prostate cancer risk calculator within a high-risk Dutch clinical cohort.

Authors:  Marinus J Hagens; Piter J Stelwagen; Hans Veerman; Sybren P Rynja; Martijn Smeenge; Vincent van der Noort; Ton A Roeleveld; Jolien van Kesteren; Sebastiaan Remmers; Monique J Roobol; Pim J van Leeuwen; Henk G van der Poel
Journal:  World J Urol       Date:  2022-10-16       Impact factor: 3.661

Review 2.  The future of early cancer detection.

Authors:  Rebecca C Fitzgerald; Antonis C Antoniou; Ljiljana Fruk; Nitzan Rosenfeld
Journal:  Nat Med       Date:  2022-04-19       Impact factor: 87.241

3.  Comparative Analysis of PSA Density and an MRI-Based Predictive Model to Improve the Selection of Candidates for Prostate Biopsy.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Richard Mast; Inés M de Torres; María E Semidey; José M Abascal; Pol Servian; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-05-11       Impact factor: 6.575

4.  Reducing Biopsies and Magnetic Resonance Imaging Scans During the Diagnostic Pathway of Prostate Cancer: Applying the Rotterdam Prostate Cancer Risk Calculator to the PRECISION Trial Data.

Authors:  Sebastiaan Remmers; Veeru Kasivisvanathan; Jan F M Verbeek; Caroline M Moore; Monique J Roobol
Journal:  Eur Urol Open Sci       Date:  2021-12-15

5.  Updating the Rotterdam Prostate Cancer Risk Calculator with Invasive Cribriform and/or Intraductal Carcinoma for Men with a Prior Negative Biopsy.

Authors:  Sebastiaan Remmers; Daan Nieboer; L Lucia Rijstenberg; Tim Hansum; Geert J L H van Leenders; Monique J Roobol
Journal:  Eur Urol Open Sci       Date:  2021-12-17

6.  Multiparametric Magnetic Resonance Imaging Grades the Aggressiveness of Prostate Cancer.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Richard Mast; Inés M de Torres; María E Semidey; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-04-05       Impact factor: 6.639

7.  Early Detection of Prostate Cancer: Self-Reported Knowledge and Attitude of Physicians in Jordan.

Authors:  Mohammad A Y Alqudah; Raneem Al-Samman; Obada Matalgah; Rana Abu Farhah
Journal:  Inquiry       Date:  2022 Jan-Dec       Impact factor: 2.099

Review 8.  Volatilomics: An Emerging and Promising Avenue for the Detection of Potential Prostate Cancer Biomarkers.

Authors:  Cristina V Berenguer; Ferdinando Pereira; Jorge A M Pereira; José S Câmara
Journal:  Cancers (Basel)       Date:  2022-08-17       Impact factor: 6.575

9.  An analysis of time trends in breast and prostate cancer mortality rates in Lithuania, 1986-2020.

Authors:  Rūta Everatt; Daiva Gudavičienė
Journal:  BMC Public Health       Date:  2022-09-23       Impact factor: 4.135

10.  The Barcelona Predictive Model of Clinically Significant Prostate Cancer.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Manel Escobar; Richard Mast; Inés M de Torres; María E Semidey; José M Abascal; Carles Sola; Pol Servian; Daniel Salvador; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-03-21       Impact factor: 6.639

  10 in total

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