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Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses
BACKGROUND: Individual patient data meta-analyses (IPDMAs) prevail as the gold standard in clinical evaluations. We investigated the distribution and epidemiological characteristics of published IPDMA articles. METHODOLOGY/PRINCIPAL FINDINGS: IPDMA articles were identified through comprehensive lite...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063791/ https://www.ncbi.nlm.nih.gov/pubmed/24945406 http://dx.doi.org/10.1371/journal.pone.0100151 |
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author | Huang, Yafang Mao, Chen Yuan, Jinqiu Yang, Zuyao Di, Mengyang Tam, Wilson Wai-san Tang, Jinling |
author_facet | Huang, Yafang Mao, Chen Yuan, Jinqiu Yang, Zuyao Di, Mengyang Tam, Wilson Wai-san Tang, Jinling |
author_sort | Huang, Yafang |
collection | PubMed |
description | BACKGROUND: Individual patient data meta-analyses (IPDMAs) prevail as the gold standard in clinical evaluations. We investigated the distribution and epidemiological characteristics of published IPDMA articles. METHODOLOGY/PRINCIPAL FINDINGS: IPDMA articles were identified through comprehensive literature searches from PubMed, Embase, and Cochrane library. Two investigators independently conducted article identification, data classification and extraction. Data related to the article characteristics were collected and analyzed descriptively. A total of 829 IPDMA articles indexed until 9 August 2012 were identified. An average of 3.7 IPDMA articles was published per year. Malignant neoplasms (267 [32.2%]) and circulatory diseases (179 [21.6%]) were the most frequently occurring topics. On average, each IPDMA article included a median of 8 studies (Interquartile range, IQR 5 to 15) involving 2,563 patients (IQR 927 to 8,349). Among 829 IPDMA articles, 229 (27.6%) did not perform a systematic search to identify related studies. In total, 207 (25.0%) sought and included individual patient data (IPD) from the “grey literature”. Only 496 (59.8%) successfully obtained IPD from all identified studies. CONCLUSIONS/SIGNIFICANCE: The number of IPDMA articles exhibited an increasing trend over the past few years and mainly focused on cancer and circulatory diseases. Our data indicated that literature searches, including grey literature and data availability were inconsistent among different IPDMA articles. Possible biases may arise. Thus, decision makers should not uncritically accept all IPDMAs. |
format | Online Article Text |
id | pubmed-4063791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40637912014-06-25 Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses Huang, Yafang Mao, Chen Yuan, Jinqiu Yang, Zuyao Di, Mengyang Tam, Wilson Wai-san Tang, Jinling PLoS One Research Article BACKGROUND: Individual patient data meta-analyses (IPDMAs) prevail as the gold standard in clinical evaluations. We investigated the distribution and epidemiological characteristics of published IPDMA articles. METHODOLOGY/PRINCIPAL FINDINGS: IPDMA articles were identified through comprehensive literature searches from PubMed, Embase, and Cochrane library. Two investigators independently conducted article identification, data classification and extraction. Data related to the article characteristics were collected and analyzed descriptively. A total of 829 IPDMA articles indexed until 9 August 2012 were identified. An average of 3.7 IPDMA articles was published per year. Malignant neoplasms (267 [32.2%]) and circulatory diseases (179 [21.6%]) were the most frequently occurring topics. On average, each IPDMA article included a median of 8 studies (Interquartile range, IQR 5 to 15) involving 2,563 patients (IQR 927 to 8,349). Among 829 IPDMA articles, 229 (27.6%) did not perform a systematic search to identify related studies. In total, 207 (25.0%) sought and included individual patient data (IPD) from the “grey literature”. Only 496 (59.8%) successfully obtained IPD from all identified studies. CONCLUSIONS/SIGNIFICANCE: The number of IPDMA articles exhibited an increasing trend over the past few years and mainly focused on cancer and circulatory diseases. Our data indicated that literature searches, including grey literature and data availability were inconsistent among different IPDMA articles. Possible biases may arise. Thus, decision makers should not uncritically accept all IPDMAs. Public Library of Science 2014-06-19 /pmc/articles/PMC4063791/ /pubmed/24945406 http://dx.doi.org/10.1371/journal.pone.0100151 Text en © 2014 Huang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Huang, Yafang Mao, Chen Yuan, Jinqiu Yang, Zuyao Di, Mengyang Tam, Wilson Wai-san Tang, Jinling Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses |
title | Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses |
title_full | Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses |
title_fullStr | Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses |
title_full_unstemmed | Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses |
title_short | Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses |
title_sort | distribution and epidemiological characteristics of published individual patient data meta-analyses |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063791/ https://www.ncbi.nlm.nih.gov/pubmed/24945406 http://dx.doi.org/10.1371/journal.pone.0100151 |
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