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The Geometric Increase in Meta-Analyses from China in the Genomic Era
Meta-analyses are increasingly popular. It is unknown whether this popularity is driven by specific countries and specific meta-analyses types. PubMed was used to identify meta-analyses since 1995 (last update 9/1/2012) and catalogue their types and country of origin. We focused more on meta-analyse...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680482/ https://www.ncbi.nlm.nih.gov/pubmed/23776510 http://dx.doi.org/10.1371/journal.pone.0065602 |
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author | Ioannidis, John P. A. Chang, Christine Q. Lam, Tram Kim Schully, Sheri D. Khoury, Muin J. |
author_facet | Ioannidis, John P. A. Chang, Christine Q. Lam, Tram Kim Schully, Sheri D. Khoury, Muin J. |
author_sort | Ioannidis, John P. A. |
collection | PubMed |
description | Meta-analyses are increasingly popular. It is unknown whether this popularity is driven by specific countries and specific meta-analyses types. PubMed was used to identify meta-analyses since 1995 (last update 9/1/2012) and catalogue their types and country of origin. We focused more on meta-analyses from China (the current top producer of meta-analyses) versus the USA (top producer until recently). The annual number of meta-analyses from China increased 40-fold between 2003 and 2011 versus 2.4-fold for the USA. The growth of Chinese meta-analyses was driven by genetics (110-fold increase in 2011 versus 2003). The HuGE Navigator identified 612 meta-analyses of genetic association studies published in 2012 from China versus only 109 from the USA. We compared in-depth 50 genetic association meta-analyses from China versus 50 from USA in 2012. Meta-analyses from China almost always used only literature-based data (92%), and focused on one or two genes (94%) and variants (78%) identified with candidate gene approaches (88%), while many USA meta-analyses used genome-wide approaches and raw data. Both groups usually concluded favorably for the presence of genetic associations (80% versus 74%), but nominal significance (P<0.05) typically sufficed in the China group. Meta-analyses from China typically neglected genome-wide data, and often included candidate gene studies published in Chinese-language journals. Overall, there is an impressive rise of meta-analyses from China, particularly on genetic associations. Since most claimed candidate gene associations are likely false-positives, there is an urgent global need to incorporate genome-wide data and state-of-the art statistical inferences to avoid a flood of false-positive genetic meta-analyses. |
format | Online Article Text |
id | pubmed-3680482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-36804822013-06-17 The Geometric Increase in Meta-Analyses from China in the Genomic Era Ioannidis, John P. A. Chang, Christine Q. Lam, Tram Kim Schully, Sheri D. Khoury, Muin J. PLoS One Research Article Meta-analyses are increasingly popular. It is unknown whether this popularity is driven by specific countries and specific meta-analyses types. PubMed was used to identify meta-analyses since 1995 (last update 9/1/2012) and catalogue their types and country of origin. We focused more on meta-analyses from China (the current top producer of meta-analyses) versus the USA (top producer until recently). The annual number of meta-analyses from China increased 40-fold between 2003 and 2011 versus 2.4-fold for the USA. The growth of Chinese meta-analyses was driven by genetics (110-fold increase in 2011 versus 2003). The HuGE Navigator identified 612 meta-analyses of genetic association studies published in 2012 from China versus only 109 from the USA. We compared in-depth 50 genetic association meta-analyses from China versus 50 from USA in 2012. Meta-analyses from China almost always used only literature-based data (92%), and focused on one or two genes (94%) and variants (78%) identified with candidate gene approaches (88%), while many USA meta-analyses used genome-wide approaches and raw data. Both groups usually concluded favorably for the presence of genetic associations (80% versus 74%), but nominal significance (P<0.05) typically sufficed in the China group. Meta-analyses from China typically neglected genome-wide data, and often included candidate gene studies published in Chinese-language journals. Overall, there is an impressive rise of meta-analyses from China, particularly on genetic associations. Since most claimed candidate gene associations are likely false-positives, there is an urgent global need to incorporate genome-wide data and state-of-the art statistical inferences to avoid a flood of false-positive genetic meta-analyses. Public Library of Science 2013-06-12 /pmc/articles/PMC3680482/ /pubmed/23776510 http://dx.doi.org/10.1371/journal.pone.0065602 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Ioannidis, John P. A. Chang, Christine Q. Lam, Tram Kim Schully, Sheri D. Khoury, Muin J. The Geometric Increase in Meta-Analyses from China in the Genomic Era |
title | The Geometric Increase in Meta-Analyses from China in the Genomic Era |
title_full | The Geometric Increase in Meta-Analyses from China in the Genomic Era |
title_fullStr | The Geometric Increase in Meta-Analyses from China in the Genomic Era |
title_full_unstemmed | The Geometric Increase in Meta-Analyses from China in the Genomic Era |
title_short | The Geometric Increase in Meta-Analyses from China in the Genomic Era |
title_sort | geometric increase in meta-analyses from china in the genomic era |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680482/ https://www.ncbi.nlm.nih.gov/pubmed/23776510 http://dx.doi.org/10.1371/journal.pone.0065602 |
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