Distribution and Epidemiological Characteristics of Published Individual Patient Data Meta-Analyses

Yafang Huang, Chen Mao, Jinqiu Yuan, Zuyao Yang, Mengyang Di, Wilson Wai-san Tam and Jinling Tang

PLOS ONE, 2014, vol. 9, issue 6, 1-8

Abstract: 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.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0100151

DOI: 10.1371/journal.pone.0100151

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