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Diagnostic Approach for Venous Thromboembolism in Cancer Patients
SIMPLE SUMMARY: Cancer patients have an increased risk of venous thromboembolic diseases, which are a major cause of morbidity and mortality in this population. The current recommended diagnostic approach consists of a systematic algorithm based on clinical probability, D-dimer measurement, and/or d...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252026/ https://www.ncbi.nlm.nih.gov/pubmed/37296993 http://dx.doi.org/10.3390/cancers15113031 |
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author | Helfer, Hélène Skaff, Yara Happe, Florent Djennaoui, Sadji Chidiac, Jean Poénou, Géraldine Righini, Marc Mahé, Isabelle |
author_facet | Helfer, Hélène Skaff, Yara Happe, Florent Djennaoui, Sadji Chidiac, Jean Poénou, Géraldine Righini, Marc Mahé, Isabelle |
author_sort | Helfer, Hélène |
collection | PubMed |
description | SIMPLE SUMMARY: Cancer patients have an increased risk of venous thromboembolic diseases, which are a major cause of morbidity and mortality in this population. The current recommended diagnostic approach consists of a systematic algorithm based on clinical probability, D-dimer measurement, and/or diagnostic imaging. Broad symptoms and elevated D-dimer levels make this diagnosis challenging in cancer patients. To improve venous thromboembolism exclusion, several approaches have been developed, such as ordering systematic imaging tests, new diagnostic algorithms based on clinical probability assessment, and adjusted D-dimer thresholds. However, there is still a lack of dedicated diagnostic algorithm specific for this population. ABSTRACT: Venous thromboembolic disease (VTE) is a common complication in cancer patients. The currently recommended VTE diagnostic approach involves a step-by-step algorithm, which is based on the assessment of clinical probability, D-dimer measurement, and/or diagnostic imaging. While this diagnostic strategy is well validated and efficient in the noncancer population, its use in cancer patients is less satisfactory. Cancer patients often present nonspecific VTE symptoms resulting in less discriminatory power of the proposed clinical prediction rules. Furthermore, D-dimer levels are often increased because of a hypercoagulable state associated with the tumor process. Consequently, the vast majority of patients require imaging tests. In order to improve VTE exclusion in cancer patients, several approaches have been developed. The first approach consists of ordering imaging tests to all patients, despite overexposing a population known to have mostly multiple comorbidities to radiations and contrast products. The second approach consists of new diagnostic algorithms based on clinical probability assessment with different D-dimer thresholds, e.g., the YEARS algorithm, which shows promise in improving the diagnosis of PE in cancer patients. The third approach uses an adjusted D-dimer threshold, to age, pretest probability, clinical criteria, or other criteria. These different diagnostic strategies have not been compared head-to-head. In conclusion, despite having several proposed diagnostic approaches to diagnose VTE in cancer patients, we still lack a dedicated diagnostic algorithm specific for this population. |
format | Online Article Text |
id | pubmed-10252026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102520262023-06-10 Diagnostic Approach for Venous Thromboembolism in Cancer Patients Helfer, Hélène Skaff, Yara Happe, Florent Djennaoui, Sadji Chidiac, Jean Poénou, Géraldine Righini, Marc Mahé, Isabelle Cancers (Basel) Article SIMPLE SUMMARY: Cancer patients have an increased risk of venous thromboembolic diseases, which are a major cause of morbidity and mortality in this population. The current recommended diagnostic approach consists of a systematic algorithm based on clinical probability, D-dimer measurement, and/or diagnostic imaging. Broad symptoms and elevated D-dimer levels make this diagnosis challenging in cancer patients. To improve venous thromboembolism exclusion, several approaches have been developed, such as ordering systematic imaging tests, new diagnostic algorithms based on clinical probability assessment, and adjusted D-dimer thresholds. However, there is still a lack of dedicated diagnostic algorithm specific for this population. ABSTRACT: Venous thromboembolic disease (VTE) is a common complication in cancer patients. The currently recommended VTE diagnostic approach involves a step-by-step algorithm, which is based on the assessment of clinical probability, D-dimer measurement, and/or diagnostic imaging. While this diagnostic strategy is well validated and efficient in the noncancer population, its use in cancer patients is less satisfactory. Cancer patients often present nonspecific VTE symptoms resulting in less discriminatory power of the proposed clinical prediction rules. Furthermore, D-dimer levels are often increased because of a hypercoagulable state associated with the tumor process. Consequently, the vast majority of patients require imaging tests. In order to improve VTE exclusion in cancer patients, several approaches have been developed. The first approach consists of ordering imaging tests to all patients, despite overexposing a population known to have mostly multiple comorbidities to radiations and contrast products. The second approach consists of new diagnostic algorithms based on clinical probability assessment with different D-dimer thresholds, e.g., the YEARS algorithm, which shows promise in improving the diagnosis of PE in cancer patients. The third approach uses an adjusted D-dimer threshold, to age, pretest probability, clinical criteria, or other criteria. These different diagnostic strategies have not been compared head-to-head. In conclusion, despite having several proposed diagnostic approaches to diagnose VTE in cancer patients, we still lack a dedicated diagnostic algorithm specific for this population. MDPI 2023-06-02 /pmc/articles/PMC10252026/ /pubmed/37296993 http://dx.doi.org/10.3390/cancers15113031 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Helfer, Hélène Skaff, Yara Happe, Florent Djennaoui, Sadji Chidiac, Jean Poénou, Géraldine Righini, Marc Mahé, Isabelle Diagnostic Approach for Venous Thromboembolism in Cancer Patients |
title | Diagnostic Approach for Venous Thromboembolism in Cancer Patients |
title_full | Diagnostic Approach for Venous Thromboembolism in Cancer Patients |
title_fullStr | Diagnostic Approach for Venous Thromboembolism in Cancer Patients |
title_full_unstemmed | Diagnostic Approach for Venous Thromboembolism in Cancer Patients |
title_short | Diagnostic Approach for Venous Thromboembolism in Cancer Patients |
title_sort | diagnostic approach for venous thromboembolism in cancer patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252026/ https://www.ncbi.nlm.nih.gov/pubmed/37296993 http://dx.doi.org/10.3390/cancers15113031 |
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