Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Yafang, Mao, Chen, Yuan, Jinqiu, Yang, Zuyao, Di, Mengyang, Tam, Wilson Wai-san, Tang, Jinling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
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
_version_ 1782321860489248768
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
work_keys_str_mv AT huangyafang distributionandepidemiologicalcharacteristicsofpublishedindividualpatientdatametaanalyses
AT maochen distributionandepidemiologicalcharacteristicsofpublishedindividualpatientdatametaanalyses
AT yuanjinqiu distributionandepidemiologicalcharacteristicsofpublishedindividualpatientdatametaanalyses
AT yangzuyao distributionandepidemiologicalcharacteristicsofpublishedindividualpatientdatametaanalyses
AT dimengyang distributionandepidemiologicalcharacteristicsofpublishedindividualpatientdatametaanalyses
AT tamwilsonwaisan distributionandepidemiologicalcharacteristicsofpublishedindividualpatientdatametaanalyses
AT tangjinling distributionandepidemiologicalcharacteristicsofpublishedindividualpatientdatametaanalyses