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A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer

Colorectal cancer (CRC) has been defined as a common malignancy due to its prevailing incidence in both males and females. Recently, the intrinsic value of microRNAs (miRNAs) with respect to early cancer diagnosis has been contentious as the diagnostic accuracy of miRNAs significantly varied across...

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Autores principales: Yan, Lin, Zhao, Wenhua, Yu, Haihua, Wang, Yansen, Liu, Yuanshui, Xie, Chao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782843/
https://www.ncbi.nlm.nih.gov/pubmed/26945359
http://dx.doi.org/10.1097/MD.0000000000002738
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author Yan, Lin
Zhao, Wenhua
Yu, Haihua
Wang, Yansen
Liu, Yuanshui
Xie, Chao
author_facet Yan, Lin
Zhao, Wenhua
Yu, Haihua
Wang, Yansen
Liu, Yuanshui
Xie, Chao
author_sort Yan, Lin
collection PubMed
description Colorectal cancer (CRC) has been defined as a common malignancy due to its prevailing incidence in both males and females. Recently, the intrinsic value of microRNAs (miRNAs) with respect to early cancer diagnosis has been contentious as the diagnostic accuracy of miRNAs significantly varied across different studies. As a result of this, this pioneer meta-analysis was proposed to address this issue. Qualified studies were obtained through electronic systematical searching in Medline, Embase, and PubMed. On the basis of the random-effects model, we calculated the pooled sensitivity (SEN), specificity (SPE), and area under the receiver operating characteristics curve (AUC) to assess the diagnostic accuracy of miRNAs. Subgroup analysis and meta-regression were implemented to determine how different confounding factors affect the overall diagnostic accuracy which were considered important sources of heterogeneity. All the statistical analyses were conducted with R 3.2.1 software. We incorporated 103 studies from 36 articles with a total of 3124 CRC patients and 2579 healthy individuals. MiRNAs have a good performance with the following pooled estimates: SEN = 0.769 (95% CI = 0.733–0.802), SPE = 0.806 (95% CI = 0.781–0.829), AUC = 0.857, and partial AUC = 0.773. As suggested by subgroup analyses and meta-regression, multiple miRNAs appeared to be more favorable than single miRNA (AUC: 0.918 > 0.813, partial AUC: 0.848 > 0.701, sensitivity = 0.853 > 0.718, specificity = 0.860 > 0.772). Compared with samples of plasma, blood, tissue, and feces, miRNA obtained from serum samples were more powerful for detecting CRC particularly in Asian. Our study provided exclusive evidence that multiple miRNAs extracted from serum samples had superior diagnostic performance over single miRNA for screening CRC. Therefore, this approach that is characterized by high specificity and noninvasive nature may assist in early diagnosis of CRC particularly in Asian.
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spelling pubmed-47828432016-03-24 A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer Yan, Lin Zhao, Wenhua Yu, Haihua Wang, Yansen Liu, Yuanshui Xie, Chao Medicine (Baltimore) 5700 Colorectal cancer (CRC) has been defined as a common malignancy due to its prevailing incidence in both males and females. Recently, the intrinsic value of microRNAs (miRNAs) with respect to early cancer diagnosis has been contentious as the diagnostic accuracy of miRNAs significantly varied across different studies. As a result of this, this pioneer meta-analysis was proposed to address this issue. Qualified studies were obtained through electronic systematical searching in Medline, Embase, and PubMed. On the basis of the random-effects model, we calculated the pooled sensitivity (SEN), specificity (SPE), and area under the receiver operating characteristics curve (AUC) to assess the diagnostic accuracy of miRNAs. Subgroup analysis and meta-regression were implemented to determine how different confounding factors affect the overall diagnostic accuracy which were considered important sources of heterogeneity. All the statistical analyses were conducted with R 3.2.1 software. We incorporated 103 studies from 36 articles with a total of 3124 CRC patients and 2579 healthy individuals. MiRNAs have a good performance with the following pooled estimates: SEN = 0.769 (95% CI = 0.733–0.802), SPE = 0.806 (95% CI = 0.781–0.829), AUC = 0.857, and partial AUC = 0.773. As suggested by subgroup analyses and meta-regression, multiple miRNAs appeared to be more favorable than single miRNA (AUC: 0.918 > 0.813, partial AUC: 0.848 > 0.701, sensitivity = 0.853 > 0.718, specificity = 0.860 > 0.772). Compared with samples of plasma, blood, tissue, and feces, miRNA obtained from serum samples were more powerful for detecting CRC particularly in Asian. Our study provided exclusive evidence that multiple miRNAs extracted from serum samples had superior diagnostic performance over single miRNA for screening CRC. Therefore, this approach that is characterized by high specificity and noninvasive nature may assist in early diagnosis of CRC particularly in Asian. Wolters Kluwer Health 2016-03-07 /pmc/articles/PMC4782843/ /pubmed/26945359 http://dx.doi.org/10.1097/MD.0000000000002738 Text en Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0, 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 5700
Yan, Lin
Zhao, Wenhua
Yu, Haihua
Wang, Yansen
Liu, Yuanshui
Xie, Chao
A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer
title A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer
title_full A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer
title_fullStr A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer
title_full_unstemmed A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer
title_short A Comprehensive Meta-Analysis of MicroRNAs for Predicting Colorectal Cancer
title_sort comprehensive meta-analysis of micrornas for predicting colorectal cancer
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782843/
https://www.ncbi.nlm.nih.gov/pubmed/26945359
http://dx.doi.org/10.1097/MD.0000000000002738
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