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Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection
Improved prostate cancer detection methods would avoid over-diagnosis of clinically indolent disease informing appropriate treatment decisions. The aims of this study were to investigate the role of a panel of Inflammation biomarkers to inform the need for a biopsy to diagnose prostate cancer. Perip...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7844261/ https://www.ncbi.nlm.nih.gov/pubmed/33510263 http://dx.doi.org/10.1038/s41598-021-81965-3 |
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author | Jalali, Amirhossein Kitching, Michael Martin, Kenneth Richardson, Ciaran Murphy, Thomas Brendan FitzGerald, Stephen Peter Watson, Ronald William Perry, Antoinette Sabrina |
author_facet | Jalali, Amirhossein Kitching, Michael Martin, Kenneth Richardson, Ciaran Murphy, Thomas Brendan FitzGerald, Stephen Peter Watson, Ronald William Perry, Antoinette Sabrina |
author_sort | Jalali, Amirhossein |
collection | PubMed |
description | Improved prostate cancer detection methods would avoid over-diagnosis of clinically indolent disease informing appropriate treatment decisions. The aims of this study were to investigate the role of a panel of Inflammation biomarkers to inform the need for a biopsy to diagnose prostate cancer. Peripheral blood serum obtained from 436 men undergoing transrectal ultrasound guided biopsy were assessed for a panel of 18 inflammatory serum biomarkers in addition to Total and Free Prostate Specific Antigen (PSA). This panel was integrated into a previously developed Irish clinical risk calculator (IPRC) for the detection of prostate cancer and high-grade prostate cancer (Gleason Score ≥ 7). Using logistic regression and multinomial regression methods, two models (Logst-RC and Multi-RC) were developed considering linear and nonlinear effects of the panel in conjunction with clinical and demographic parameters for determination of the two endpoints. Both models significantly improved the predictive ability of the clinical model for detection of prostate cancer (from 0.656 to 0.731 for Logst-RC and 0.713 for Multi-RC) and high-grade prostate cancer (from 0.716 to 0.785 for Logst-RC and 0.767 for Multi-RC) and demonstrated higher clinical net benefit. This improved discriminatory power and clinical utility may allow for individualised risk stratification improving clinical decision making. |
format | Online Article Text |
id | pubmed-7844261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78442612021-02-01 Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection Jalali, Amirhossein Kitching, Michael Martin, Kenneth Richardson, Ciaran Murphy, Thomas Brendan FitzGerald, Stephen Peter Watson, Ronald William Perry, Antoinette Sabrina Sci Rep Article Improved prostate cancer detection methods would avoid over-diagnosis of clinically indolent disease informing appropriate treatment decisions. The aims of this study were to investigate the role of a panel of Inflammation biomarkers to inform the need for a biopsy to diagnose prostate cancer. Peripheral blood serum obtained from 436 men undergoing transrectal ultrasound guided biopsy were assessed for a panel of 18 inflammatory serum biomarkers in addition to Total and Free Prostate Specific Antigen (PSA). This panel was integrated into a previously developed Irish clinical risk calculator (IPRC) for the detection of prostate cancer and high-grade prostate cancer (Gleason Score ≥ 7). Using logistic regression and multinomial regression methods, two models (Logst-RC and Multi-RC) were developed considering linear and nonlinear effects of the panel in conjunction with clinical and demographic parameters for determination of the two endpoints. Both models significantly improved the predictive ability of the clinical model for detection of prostate cancer (from 0.656 to 0.731 for Logst-RC and 0.713 for Multi-RC) and high-grade prostate cancer (from 0.716 to 0.785 for Logst-RC and 0.767 for Multi-RC) and demonstrated higher clinical net benefit. This improved discriminatory power and clinical utility may allow for individualised risk stratification improving clinical decision making. Nature Publishing Group UK 2021-01-28 /pmc/articles/PMC7844261/ /pubmed/33510263 http://dx.doi.org/10.1038/s41598-021-81965-3 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jalali, Amirhossein Kitching, Michael Martin, Kenneth Richardson, Ciaran Murphy, Thomas Brendan FitzGerald, Stephen Peter Watson, Ronald William Perry, Antoinette Sabrina Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection |
title | Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection |
title_full | Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection |
title_fullStr | Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection |
title_full_unstemmed | Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection |
title_short | Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection |
title_sort | integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7844261/ https://www.ncbi.nlm.nih.gov/pubmed/33510263 http://dx.doi.org/10.1038/s41598-021-81965-3 |
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