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Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism
OBJECTIVE: This study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer. METHODS: Data from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analy...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7645363/ https://www.ncbi.nlm.nih.gov/pubmed/31885320 http://dx.doi.org/10.1177/0300060519893173 |
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author | Wang, Xindan Huang, Jing Bingbing, Zhao Li, Shape Li, Li |
author_facet | Wang, Xindan Huang, Jing Bingbing, Zhao Li, Shape Li, Li |
author_sort | Wang, Xindan |
collection | PubMed |
description | OBJECTIVE: This study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer. METHODS: Data from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analyzed. Patients were risk-stratified with three different risk assessment models individually, including the Caprini model, Wells DVT model, and Khorana model. RESULTS: The difference in risk level evaluated by the Caprini model was not different between the DVT and control groups. However, the DVT group had a significantly higher risk level than the control group with the Wells DVT or Khorana model. The Wells DVT model was more effective for stratifying patients in the DVT group into the higher risk level and for stratifying those in the control group into the lower risk level. Receiver operating curve analysis showed that the area under the curve of the Wells DVT, Khorana, and Caprini models was 0.995 ± 0.002, 0.642 ± 0.038, and 0.567 ± 0.039, respectively. CONCLUSION: The Wells DVT model is the most suitable risk assessment model for predicting DVT. Clinicians could also combine the Caprini and Wells DVT models to effectively identify high-risk patients and eliminate patients without DVT. |
format | Online Article Text |
id | pubmed-7645363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-76453632020-11-17 Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism Wang, Xindan Huang, Jing Bingbing, Zhao Li, Shape Li, Li J Int Med Res Retrospective Clinical Research Report OBJECTIVE: This study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer. METHODS: Data from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analyzed. Patients were risk-stratified with three different risk assessment models individually, including the Caprini model, Wells DVT model, and Khorana model. RESULTS: The difference in risk level evaluated by the Caprini model was not different between the DVT and control groups. However, the DVT group had a significantly higher risk level than the control group with the Wells DVT or Khorana model. The Wells DVT model was more effective for stratifying patients in the DVT group into the higher risk level and for stratifying those in the control group into the lower risk level. Receiver operating curve analysis showed that the area under the curve of the Wells DVT, Khorana, and Caprini models was 0.995 ± 0.002, 0.642 ± 0.038, and 0.567 ± 0.039, respectively. CONCLUSION: The Wells DVT model is the most suitable risk assessment model for predicting DVT. Clinicians could also combine the Caprini and Wells DVT models to effectively identify high-risk patients and eliminate patients without DVT. SAGE Publications 2019-12-29 /pmc/articles/PMC7645363/ /pubmed/31885320 http://dx.doi.org/10.1177/0300060519893173 Text en © The Author(s) 2019 https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Retrospective Clinical Research Report Wang, Xindan Huang, Jing Bingbing, Zhao Li, Shape Li, Li Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
title | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
title_full | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
title_fullStr | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
title_full_unstemmed | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
title_short | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
title_sort | risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
topic | Retrospective Clinical Research Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7645363/ https://www.ncbi.nlm.nih.gov/pubmed/31885320 http://dx.doi.org/10.1177/0300060519893173 |
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