Literature DB >> 28753865

Prognostic Biomarkers Used for Localised Prostate Cancer Management: A Systematic Review.

Pierre-Jean Lamy1, Yves Allory2, Anne-Sophie Gauchez3, Bernard Asselain4, Philippe Beuzeboc5, Patricia de Cremoux6, Jacqueline Fontugne7, Agnès Georges8, Christophe Hennequin6, Jacqueline Lehmann-Che6, Christophe Massard9, Ingrid Millet10, Thibaut Murez11, Marie-Hélène Schlageter12, Olivier Rouvière13, Diana Kassab-Chahmi14, François Rozet15, Jean-Luc Descotes16, Xavier Rébillard17.   

Abstract

CONTEXT: Prostate cancer stratification is based on tumour size, pretreatment PSA level, and Gleason score, but it remains imperfect. Current research focuses on the discovery and validation of novel prognostic biomarkers to improve the identification of patients at risk of aggressive cancer or of tumour relapse.
OBJECTIVE: This systematic review by the Intergroupe Coopérateur Francophone de Recherche en Onco-urologie (ICFuro) analysed new evidence on the analytical validity and clinical validity and utility of six prognostic biomarkers (PHI, 4Kscore, MiPS, GPS, Prolaris, Decipher). EVIDENCE ACQUISITION: All available data for the six biomarkers published between January 2002 and April 2015 were systematically searched and reviewed. The main endpoints were aggressive prostate cancer prediction, additional value compared to classical prognostic parameters, and clinical benefit for patients with localised prostate cancer. EVIDENCE SYNTHESIS: The preanalytical and analytical validations were heterogeneous for all tests and often not adequate for the molecular signatures. Each biomarker was studied for specific indications (candidates for a first or second biopsy, and potential candidates for active surveillance, radical prostatectomy, or adjuvant treatment) for which the level of evidence (LOE) was variable. PHI and 4Kscore were the biomarkers with the highest LOE for discriminating aggressive and indolent tumours in different indications.
CONCLUSIONS: Blood biomarkers (PHI and 4Kscore) have the highest LOE for the prediction of more aggressive prostate cancer and could help clinicians to manage patients with localised prostate cancer. The other biomarkers show a potential prognostic value; however, they should be evaluated in additional studies to confirm their clinical validity. PATIENT
SUMMARY: We reviewed studies assessing the value of six prognostic biomarkers for prostate cancer. On the basis of the available evidence, some biomarkers could help in discriminating between aggressive and non-aggressive tumours with an additional value compared to the prognostic parameters currently used by clinicians.
Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Active surveillance; Biomarkers; Genomic signature; Prognosis; Prostate cancer

Mesh:

Substances:

Year:  2017        PMID: 28753865     DOI: 10.1016/j.euf.2017.02.017

Source DB:  PubMed          Journal:  Eur Urol Focus        ISSN: 2405-4569


  20 in total

1.  Ultrasensitive prostate-specific antigen level as a predictor of biochemical progression after robot-assisted radical prostatectomy: Towards risk adapted follow-up.

Authors:  Nikolaos Grivas; Daan de Bruin; Kurdo Barwari; Erik van Muilekom; Corinne Tillier; Pim J van Leeuwen; Esther Wit; Wouter Kroese; Henk van der Poel
Journal:  J Clin Lab Anal       Date:  2018-10-26       Impact factor: 2.352

2.  Differentiating Molecular Risk Assessments for Prostate Cancer.

Authors:  Benjamin Press; Michael Schulster; Marc A Bjurlin
Journal:  Rev Urol       Date:  2018

3.  Value of Intact Prostate Specific Antigen and Human Kallikrein 2 in the 4 Kallikrein Predictive Model: An Individual Patient Data Meta-Analysis.

Authors:  Andrew Vickers; Emily A Vertosick; Daniel D Sjoberg; Freddie Hamdy; David Neal; Anders Bjartell; Jonas Hugosson; Jenny L Donovan; Arnauld Villers; Stephen Zappala; Hans Lilja
Journal:  J Urol       Date:  2018-01-31       Impact factor: 7.450

Review 4.  Is perfect the enemy of good? Weighing the evidence for biparametric MRI in prostate cancer.

Authors:  Alexander P Cole; Bjoern J Langbein; Francesco Giganti; Fiona M Fennessy; Clare M Tempany; Mark Emberton
Journal:  Br J Radiol       Date:  2021-12-16       Impact factor: 3.039

Review 5.  The future of prostate cancer research: bringing data together, looking back and forward.

Authors:  Chris Bangma; Henk Obbink
Journal:  Transl Androl Urol       Date:  2018-02

Review 6.  Multi-disciplinary and shared decision-making approach in the management of organ-confined prostate cancer.

Authors:  Syed M Nazim; Mohamed Fawzy; Christian Bach; M Hammad Ather
Journal:  Arab J Urol       Date:  2018-08-06

7.  Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence.

Authors:  Yanzhi Jiang; Wenjuan Mei; Yan Gu; Xiaozeng Lin; Lizhi He; Hui Zeng; Fengxiang Wei; Xinhong Wan; Huixiang Yang; Pierre Major; Damu Tang
Journal:  Mol Oncol       Date:  2018-08-11       Impact factor: 6.603

8.  The Ability of Prostate Health Index (PHI) to Predict Gleason Score in Patients With Prostate Cancer and Discriminate Patients Between Gleason Score 6 and Gleason Score Higher Than 6-A Study on 320 Patients After Radical Prostatectomy.

Authors:  Olga Dolejsova; Radek Kucera; Radka Fuchsova; Ondrej Topolcan; Hana Svobodova; Ondrej Hes; Viktor Eret; Ladislav Pecen; Milan Hora
Journal:  Technol Cancer Res Treat       Date:  2018-01-01

9.  Independent Evaluation of the Respective Predictive Values for High-Grade Prostate Cancer of Clinical Information and RNA Biomarkers after Upfront MRI and Image-Guided Biopsies.

Authors:  Mathieu Roumiguié; Guillaume Ploussard; Léonor Nogueira; Eric Bruguière; Olivier Meyrignac; Marine Lesourd; Sarah Péricart; Bernard Malavaud
Journal:  Cancers (Basel)       Date:  2020-01-24       Impact factor: 6.639

10.  Proteomic Tissue-Based Classifier for Early Prediction of Prostate Cancer Progression.

Authors:  Yuqian Gao; Yi-Ting Wang; Yongmei Chen; Hui Wang; Denise Young; Tujin Shi; Yingjie Song; Athena A Schepmoes; Claire Kuo; Thomas L Fillmore; Wei-Jun Qian; Richard D Smith; Sudhir Srivastava; Jacob Kagan; Albert Dobi; Isabell A Sesterhenn; Inger L Rosner; Gyorgy Petrovics; Karin D Rodland; Shiv Srivastava; Jennifer Cullen; Tao Liu
Journal:  Cancers (Basel)       Date:  2020-05-17       Impact factor: 6.639

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