发表的个体患者数据荟萃分析的分布和流行病学特征。
Distribution and epidemiological characteristics of published individual patient data meta-analyses.
机构信息
Division of Epidemiology, The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
Division of Epidemiology, The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China; The Shenzhen Municipal Key Laboratory for Health Risk Analysis, Shenzhen Research Institute of The Chinese University of Hong Kong, Shenzhen, Guangdong Province, China.
出版信息
PLoS One. 2014 Jun 19;9(6):e100151. doi: 10.1371/journal.pone.0100151. eCollection 2014.
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.
背景
个体患者数据荟萃分析（IPDMA）作为临床评估的金标准而流行。我们调查了已发表的 IPDMA 文章的分布和流行病学特征。
方法/主要发现：通过全面的文献检索，从 PubMed、Embase 和 Cochrane 图书馆中确定了 IPDMA 文章。两名调查员独立进行文章识别、数据分类和提取。收集并描述性地分析与文章特征相关的数据。截至 2012 年 8 月 9 日，共确定了 829 篇 IPDMA 文章。平均每年发表 3.7 篇 IPDMA 文章。恶性肿瘤（267 [32.2%]）和循环系统疾病（179 [21.6%]）是最常出现的主题。平均而言，每篇 IPDMA 文章包含中位数为 8 项研究（四分位距，IQR 5 至 15），涉及 2563 名患者（IQR 927 至 8349）。在 829 篇 IPDMA 文章中，229 篇（27.6%）没有进行系统搜索以确定相关研究。总共 207 篇（25.0%）从“灰色文献”中寻找并包括了个体患者数据（IPD）。只有 496 篇（59.8%）成功从所有确定的研究中获得了 IPD。
结论/意义：过去几年，IPDMA 文章的数量呈上升趋势，主要集中在癌症和循环系统疾病上。我们的数据表明，不同的 IPDMA 文章的文献检索，包括灰色文献和数据可用性存在不一致性。可能会出现偏差。因此，决策者不应盲目接受所有的 IPDMA。
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