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Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis
BACKGROUND: In developed nations, ovarian cancer has resulted in the most fatalities from gynecological cancer. Laparoscopy is primarily utilized as the test to diagnose ovarian cancer. Besides being costly, there are surgical risks associated with laparoscopies. At present, clinical practitioners h...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738010/ https://www.ncbi.nlm.nih.gov/pubmed/33327306 http://dx.doi.org/10.1097/MD.0000000000023551 |
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author | Su, Yongxue Deng, Lingli Yang, Lijun Yuan, Xianhong Xia, Wei Liu, Ping |
author_facet | Su, Yongxue Deng, Lingli Yang, Lijun Yuan, Xianhong Xia, Wei Liu, Ping |
author_sort | Su, Yongxue |
collection | PubMed |
description | BACKGROUND: In developed nations, ovarian cancer has resulted in the most fatalities from gynecological cancer. Laparoscopy is primarily utilized as the test to diagnose ovarian cancer. Besides being costly, there are surgical risks associated with laparoscopies. At present, clinical practitioners have access to non-invasive tests for diagnosing ovarian cancer. This study aims to evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) for diagnosing ovarian cancer. METHODS: In order to obtain eligible studies, cross-sectional studies or randomized controlled trials are searched in electronic databases. The databases include 5 English databases (PubMed, the Cochrane Library, PsycINFO, EMBASE, and Web of Science) and 3 Chinese databases (China Biomedical Literature Database, China National Knowledge Infrastructure, and WanFang database). The databases are searched from their origin to October 2020. Quality Assessment of Diagnostic Accuracy Studies-2 is used to assess the methodological quality of the selected studies. RevMan 5.3 and SAS NLMIXED software are used to assess the data synthesis, sensitivity analysis, and risk of bias assessment. RESULTS: This study evaluates the pooled diagnostic value of MRI for diagnosing ovarian cancer. CONCLUSIONS: This study will summarize previously published evidence of MRI in relation to diagnosing ovarian cancer. ETHICS AND DISSEMINATION: Since this study does not utilize data from patients, this protocol does not require ethical approval. PROTOCOL REGISTRATION NUMBER: DOI 10.17605/OSF.IO/A6SPQ (https://osf.io/a6spq) |
format | Online Article Text |
id | pubmed-7738010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-77380102020-12-16 Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis Su, Yongxue Deng, Lingli Yang, Lijun Yuan, Xianhong Xia, Wei Liu, Ping Medicine (Baltimore) 3700 BACKGROUND: In developed nations, ovarian cancer has resulted in the most fatalities from gynecological cancer. Laparoscopy is primarily utilized as the test to diagnose ovarian cancer. Besides being costly, there are surgical risks associated with laparoscopies. At present, clinical practitioners have access to non-invasive tests for diagnosing ovarian cancer. This study aims to evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) for diagnosing ovarian cancer. METHODS: In order to obtain eligible studies, cross-sectional studies or randomized controlled trials are searched in electronic databases. The databases include 5 English databases (PubMed, the Cochrane Library, PsycINFO, EMBASE, and Web of Science) and 3 Chinese databases (China Biomedical Literature Database, China National Knowledge Infrastructure, and WanFang database). The databases are searched from their origin to October 2020. Quality Assessment of Diagnostic Accuracy Studies-2 is used to assess the methodological quality of the selected studies. RevMan 5.3 and SAS NLMIXED software are used to assess the data synthesis, sensitivity analysis, and risk of bias assessment. RESULTS: This study evaluates the pooled diagnostic value of MRI for diagnosing ovarian cancer. CONCLUSIONS: This study will summarize previously published evidence of MRI in relation to diagnosing ovarian cancer. ETHICS AND DISSEMINATION: Since this study does not utilize data from patients, this protocol does not require ethical approval. PROTOCOL REGISTRATION NUMBER: DOI 10.17605/OSF.IO/A6SPQ (https://osf.io/a6spq) Lippincott Williams & Wilkins 2020-12-11 /pmc/articles/PMC7738010/ /pubmed/33327306 http://dx.doi.org/10.1097/MD.0000000000023551 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 |
spellingShingle | 3700 Su, Yongxue Deng, Lingli Yang, Lijun Yuan, Xianhong Xia, Wei Liu, Ping Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis |
title | Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis |
title_full | Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis |
title_fullStr | Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis |
title_full_unstemmed | Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis |
title_short | Magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: A protocol for systematic review and meta-analysis |
title_sort | magnetic resonance imaging for the non-invasive diagnosis in patients with ovarian cancer: a protocol for systematic review and meta-analysis |
topic | 3700 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738010/ https://www.ncbi.nlm.nih.gov/pubmed/33327306 http://dx.doi.org/10.1097/MD.0000000000023551 |
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