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Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated?
Risk-based patient selection for systematic biopsy in prostate cancer diagnosis has been adopted in daily clinical practice, either by clinical judgment and PSA testing, or using multivariate risk prediction tools. The use of multivariable risk prediction tools can significantly reduce unnecessary s...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064475/ https://www.ncbi.nlm.nih.gov/pubmed/31399825 http://dx.doi.org/10.1007/s00345-019-02899-0 |
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author | Schoots, Ivo G. Padhani, Anwar R. |
author_facet | Schoots, Ivo G. Padhani, Anwar R. |
author_sort | Schoots, Ivo G. |
collection | PubMed |
description | Risk-based patient selection for systematic biopsy in prostate cancer diagnosis has been adopted in daily clinical practice, either by clinical judgment and PSA testing, or using multivariate risk prediction tools. The use of multivariable risk prediction tools can significantly reduce unnecessary systematic biopsies, without compromising the detection of clinically significant disease. Increasingly multi-parametric magnetic resonance imaging (MRI) is performed, not only in men with a persistent suspicion of prostate cancer after prior negative systematic biopsy, but also at initial screening before the first biopsy. The combination of MRI and multivariate risk prediction tools could potentially enhance prostate cancer diagnosis using multivariate MRI incorporated risk-based models to decide on the need for prostate MRI, but also using MRI results to adjusted risk-based models, and to guide MRI-directed biopsies. In this review, we discuss the diagnostic work-up for clinically significant prostate cancer, where the combination of MRI and multivariate risk prediction tools is integrated, and how together they can contribute to personalized diagnosis. |
format | Online Article Text |
id | pubmed-7064475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-70644752020-03-23 Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? Schoots, Ivo G. Padhani, Anwar R. World J Urol Topic Paper Risk-based patient selection for systematic biopsy in prostate cancer diagnosis has been adopted in daily clinical practice, either by clinical judgment and PSA testing, or using multivariate risk prediction tools. The use of multivariable risk prediction tools can significantly reduce unnecessary systematic biopsies, without compromising the detection of clinically significant disease. Increasingly multi-parametric magnetic resonance imaging (MRI) is performed, not only in men with a persistent suspicion of prostate cancer after prior negative systematic biopsy, but also at initial screening before the first biopsy. The combination of MRI and multivariate risk prediction tools could potentially enhance prostate cancer diagnosis using multivariate MRI incorporated risk-based models to decide on the need for prostate MRI, but also using MRI results to adjusted risk-based models, and to guide MRI-directed biopsies. In this review, we discuss the diagnostic work-up for clinically significant prostate cancer, where the combination of MRI and multivariate risk prediction tools is integrated, and how together they can contribute to personalized diagnosis. Springer Berlin Heidelberg 2019-08-09 2020 /pmc/articles/PMC7064475/ /pubmed/31399825 http://dx.doi.org/10.1007/s00345-019-02899-0 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Topic Paper Schoots, Ivo G. Padhani, Anwar R. Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? |
title | Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? |
title_full | Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? |
title_fullStr | Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? |
title_full_unstemmed | Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? |
title_short | Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? |
title_sort | personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate mri be incorporated? |
topic | Topic Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064475/ https://www.ncbi.nlm.nih.gov/pubmed/31399825 http://dx.doi.org/10.1007/s00345-019-02899-0 |
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