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Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer
In current practice, prostate cancer staging alone is not sufficient to adequately assess the patient’s prognosis and plan the management strategies. Multiple clinicopathological parameters and risk tools for prostate cancer have been developed over the past decades to better characterize the diseas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7564222/ https://www.ncbi.nlm.nih.gov/pubmed/32957584 http://dx.doi.org/10.3390/cells9092116 |
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author | Saoud, Ragheed Heidar, Nassib Abou Cimadamore, Alessia Paner, Gladell P. |
author_facet | Saoud, Ragheed Heidar, Nassib Abou Cimadamore, Alessia Paner, Gladell P. |
author_sort | Saoud, Ragheed |
collection | PubMed |
description | In current practice, prostate cancer staging alone is not sufficient to adequately assess the patient’s prognosis and plan the management strategies. Multiple clinicopathological parameters and risk tools for prostate cancer have been developed over the past decades to better characterize the disease and provide an enhanced assessment of prognosis. Herein, we review novel prognostic biomarkers and their integration into risk assessment models for prostate cancer focusing on their capability to help avoid unnecessary imaging studies, biopsies and diagnosis of low risk prostate cancers, to help in the decision-making process between active surveillance and treatment intervention, and to predict recurrence after radical prostatectomy. There is an imperative need of reliable biomarkers to stratify prostate cancer patients that may benefit from different management approaches. The integration of biomarkers panel with risk assessment models appears to improve prostate cancer diagnosis and management. However, integration of novel genomic biomarkers in future prognostic models requires further validation in their clinical efficacy, standardization, and cost-effectiveness in routine application. |
format | Online Article Text |
id | pubmed-7564222 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75642222020-10-26 Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer Saoud, Ragheed Heidar, Nassib Abou Cimadamore, Alessia Paner, Gladell P. Cells Review In current practice, prostate cancer staging alone is not sufficient to adequately assess the patient’s prognosis and plan the management strategies. Multiple clinicopathological parameters and risk tools for prostate cancer have been developed over the past decades to better characterize the disease and provide an enhanced assessment of prognosis. Herein, we review novel prognostic biomarkers and their integration into risk assessment models for prostate cancer focusing on their capability to help avoid unnecessary imaging studies, biopsies and diagnosis of low risk prostate cancers, to help in the decision-making process between active surveillance and treatment intervention, and to predict recurrence after radical prostatectomy. There is an imperative need of reliable biomarkers to stratify prostate cancer patients that may benefit from different management approaches. The integration of biomarkers panel with risk assessment models appears to improve prostate cancer diagnosis and management. However, integration of novel genomic biomarkers in future prognostic models requires further validation in their clinical efficacy, standardization, and cost-effectiveness in routine application. MDPI 2020-09-17 /pmc/articles/PMC7564222/ /pubmed/32957584 http://dx.doi.org/10.3390/cells9092116 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Saoud, Ragheed Heidar, Nassib Abou Cimadamore, Alessia Paner, Gladell P. Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer |
title | Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer |
title_full | Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer |
title_fullStr | Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer |
title_full_unstemmed | Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer |
title_short | Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer |
title_sort | incorporating prognostic biomarkers into risk assessment models and tnm staging for prostate cancer |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7564222/ https://www.ncbi.nlm.nih.gov/pubmed/32957584 http://dx.doi.org/10.3390/cells9092116 |
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