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CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy
BACKGROUND: Non-small-cell lung cancer (NSCLC) is a rare cancer in lung carcinomas and has been widely known as a difficult curable disease among all the tumors. However, early detection of malignant potential in patients with NSCLC has still been a huge challenge all around the world. CT, MRI, and...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6160194/ https://www.ncbi.nlm.nih.gov/pubmed/30235705 http://dx.doi.org/10.1097/MD.0000000000012387 |
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author | Zhang, Yi Ni, Jinman Wei, Kongyuan Tian, Jinhui Sun, Shaobo |
author_facet | Zhang, Yi Ni, Jinman Wei, Kongyuan Tian, Jinhui Sun, Shaobo |
author_sort | Zhang, Yi |
collection | PubMed |
description | BACKGROUND: Non-small-cell lung cancer (NSCLC) is a rare cancer in lung carcinomas and has been widely known as a difficult curable disease among all the tumors. However, early detection of malignant potential in patients with NSCLC has still been a huge challenge all around the world. CT, MRI, and F-18 FDG PET are all considered as good tests for diagnosing malignant NSCLC efficiently, but no recommended suggestion presents that which test among the 3 is the prior one in diagnose. We perform this study through network meta-analysis method, and to rank these tests using a superiority index. METHODS AND ANALYSIS: PubMed, Embase.com, and the Cochrane Central Register of Controlled Trials (CENTRAL) will be searched from their inception to March 2018. We will include diagnostic tests which assessed the accuracy of CT, MRI, and F-18 FDG PET for diagnosing NSCLC. The risk of bias for each study will be independently assessed as low, moderate, or high using criteria adapted from Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Network meta-analysis will be performed using STATA 12.0 and R 3.4.1 software. The competing diagnostic tests will be ranked by a superiority index. RESULTS: This study is ongoing, and will be submitted to a peer-reviewed journal for publication. CONCLUSION: This study will provide systematically suggestions to select different diagnostic measures for detecting the early NSCLC. ETHICS AND DISSEMINATION: Ethical approval and patient consent are not required since this study is a network meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for publication. PROSPERO REGISTRATION NUMBER: PROSPEROCRD42018094542. |
format | Online Article Text |
id | pubmed-6160194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-61601942018-10-12 CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy Zhang, Yi Ni, Jinman Wei, Kongyuan Tian, Jinhui Sun, Shaobo Medicine (Baltimore) Research Article BACKGROUND: Non-small-cell lung cancer (NSCLC) is a rare cancer in lung carcinomas and has been widely known as a difficult curable disease among all the tumors. However, early detection of malignant potential in patients with NSCLC has still been a huge challenge all around the world. CT, MRI, and F-18 FDG PET are all considered as good tests for diagnosing malignant NSCLC efficiently, but no recommended suggestion presents that which test among the 3 is the prior one in diagnose. We perform this study through network meta-analysis method, and to rank these tests using a superiority index. METHODS AND ANALYSIS: PubMed, Embase.com, and the Cochrane Central Register of Controlled Trials (CENTRAL) will be searched from their inception to March 2018. We will include diagnostic tests which assessed the accuracy of CT, MRI, and F-18 FDG PET for diagnosing NSCLC. The risk of bias for each study will be independently assessed as low, moderate, or high using criteria adapted from Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Network meta-analysis will be performed using STATA 12.0 and R 3.4.1 software. The competing diagnostic tests will be ranked by a superiority index. RESULTS: This study is ongoing, and will be submitted to a peer-reviewed journal for publication. CONCLUSION: This study will provide systematically suggestions to select different diagnostic measures for detecting the early NSCLC. ETHICS AND DISSEMINATION: Ethical approval and patient consent are not required since this study is a network meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for publication. PROSPERO REGISTRATION NUMBER: PROSPEROCRD42018094542. Wolters Kluwer Health 2018-09-21 /pmc/articles/PMC6160194/ /pubmed/30235705 http://dx.doi.org/10.1097/MD.0000000000012387 Text en Copyright © 2018 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 | Research Article Zhang, Yi Ni, Jinman Wei, Kongyuan Tian, Jinhui Sun, Shaobo CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy |
title | CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy |
title_full | CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy |
title_fullStr | CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy |
title_full_unstemmed | CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy |
title_short | CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy |
title_sort | ct, mri, and f-18 fdg pet for the detection of non-small-cell lung cancer (nsclc): a protocol for a network meta-analysis of diagnostic test accuracy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6160194/ https://www.ncbi.nlm.nih.gov/pubmed/30235705 http://dx.doi.org/10.1097/MD.0000000000012387 |
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