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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...

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Autores principales: Su, Yongxue, Deng, Lingli, Yang, Lijun, Yuan, Xianhong, Xia, Wei, Liu, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2020
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)
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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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