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Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models
Risk prediction of chemotherapy-associated venous thromboembolism (VTE) is a compelling challenge in contemporary oncology, as VTE may result in treatment delays, impaired quality of life, and increased mortality. Current guidelines do not recommend thromboprophylaxis for primary prevention, but ass...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356247/ https://www.ncbi.nlm.nih.gov/pubmed/30650562 http://dx.doi.org/10.3390/cancers11010095 |
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author | Riondino, Silvia Ferroni, Patrizia Zanzotto, Fabio Massimo Roselli, Mario Guadagni, Fiorella |
author_facet | Riondino, Silvia Ferroni, Patrizia Zanzotto, Fabio Massimo Roselli, Mario Guadagni, Fiorella |
author_sort | Riondino, Silvia |
collection | PubMed |
description | Risk prediction of chemotherapy-associated venous thromboembolism (VTE) is a compelling challenge in contemporary oncology, as VTE may result in treatment delays, impaired quality of life, and increased mortality. Current guidelines do not recommend thromboprophylaxis for primary prevention, but assessment of the patient’s individual risk of VTE prior to chemotherapy is generally advocated. In recent years, efforts have been devoted to building accurate predictive tools for VTE risk assessment in cancer patients. This review focuses on candidate biomarkers and prediction models currently under investigation, considering their advantages and disadvantages, and discussing their diagnostic performance and potential pitfalls. |
format | Online Article Text |
id | pubmed-6356247 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63562472019-02-05 Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models Riondino, Silvia Ferroni, Patrizia Zanzotto, Fabio Massimo Roselli, Mario Guadagni, Fiorella Cancers (Basel) Review Risk prediction of chemotherapy-associated venous thromboembolism (VTE) is a compelling challenge in contemporary oncology, as VTE may result in treatment delays, impaired quality of life, and increased mortality. Current guidelines do not recommend thromboprophylaxis for primary prevention, but assessment of the patient’s individual risk of VTE prior to chemotherapy is generally advocated. In recent years, efforts have been devoted to building accurate predictive tools for VTE risk assessment in cancer patients. This review focuses on candidate biomarkers and prediction models currently under investigation, considering their advantages and disadvantages, and discussing their diagnostic performance and potential pitfalls. MDPI 2019-01-15 /pmc/articles/PMC6356247/ /pubmed/30650562 http://dx.doi.org/10.3390/cancers11010095 Text en © 2019 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 Riondino, Silvia Ferroni, Patrizia Zanzotto, Fabio Massimo Roselli, Mario Guadagni, Fiorella Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models |
title | Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models |
title_full | Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models |
title_fullStr | Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models |
title_full_unstemmed | Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models |
title_short | Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models |
title_sort | predicting vte in cancer patients: candidate biomarkers and risk assessment models |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356247/ https://www.ncbi.nlm.nih.gov/pubmed/30650562 http://dx.doi.org/10.3390/cancers11010095 |
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