Cochrane Centralised Search Service showed high sensitivity identifying randomized controlled trials: A retrospective analysis
Cochrane Centralised Search Service showed high sensitivity identifying randomized controlled trials: A retrospective analysis
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DOI：
10.1016/j.jclinepi.2020.08.008
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发表时间：
2020-11-01
影响因子：
7.2
通讯作者：
Foxlee, R.
中科院分区：
文献类型：
--
作者：
Noel-Storr, A. H.;Dooley, G.;Foxlee, R.
背景和目标：对照试验的科克伦中心注册库（CENTRAL）是从多个来源汇编而成的，包括PubMed和Embase。自2017年以来，我们通过使用应用程序编程接口、机器学习和众包，增加了CENTRAL的数据源数量，并提高了流程效率。我们的目标有两个：（一）评估科克伦集中检索和筛选流程的有效性，以正确识别符合纳入随机对照研究的科克伦系统评价的已发表报告的参考文献。对照试验（RCT）。(2)确定机会，以提高性能的科克伦的集中搜索和筛选过程，以确定参考eligible trials.Methods：我们确定了所有的RCT参考文献（无论是发表的期刊文章或试验注册记录）的出版或注册日期之间的1 ST 2017年1月和31 ST 2018年12月已被纳入科克伦干预审查。然后，我们查看了每个纳入参考文献的审计跟踪，以确定它是否已被我们的集中检索过程识别，并随后添加到CENTRAL.Results：我们确定了650篇纳入研究的参考文献，其出版年份为2017年或2018年。其中，634个（97.5%）被科克伦的集中搜索服务捕获。科克伦的集中检索服务遗漏了16篇参考文献：6篇为PubMed非MEDLINE状态，4篇被集中Embase检索遗漏，3篇被科克伦Crowd错误分类，1篇来自MEDLINE或Embase中未编入索引的期刊，1篇仅在2019年添加到Embase，1篇参考文献被自动RCT机器学习分类器拒绝。在16个遗漏的参考文献中，有8个是主要的或唯一的出版物，以试验在审查中，它已被包括在内。结论：这项分析表明，科克伦的集中搜索和筛选过程是高度敏感的。它还帮助我们更好地理解为什么一些合格的RCT被遗漏。CSS在帮助填充CENTRAL方面发挥着关键作用，并正在推动我们使CENTRAL成为RCT的综合存储库。(c)2020年，任作家。由爱思唯尔公司出版这是一篇基于CC BY-NC-ND许可证的开放获取文章（http：creativecommons.org/licenses/by-nc-nd/4）。0/）。
Background and objectives: The Cochrane Central Register of Controlled Trials (CENTRAL) is compiled from a number of sources, including PubMed and Embase. Since 2017, we have increased the number of sources feeding into CENTRAL and improved the efficiency of our processes through the use of application programming interfaces, machine learning, and crowdsourcing.Our objectives were twofold: (1) Assess the effectiveness of Cochrane's centralized search and screening processes to correctly identify references to published reports which are eligible for inclusion in Cochrane systematic reviews of randomized controlled trials (RCTs). (2) Identify opportunities to improve the performance of Cochrane's centralized search and screening processes to identify references to eligible trials.Methods: We identified all references to RCTs (either published journal articles or trial registration records) with a publication or registration date between 1st January 2017 and 31st December 2018 that had been included in a Cochrane intervention review. We then viewed an audit trail for each included reference to determine if it had been identified by our centralized search process and subsequently added to CENTRAL.Results: We identified 650 references to included studies with a publication year of 2017 or 2018. Of those, 634 (97.5%) had been captured by Cochrane's Centralised Search Service. Sixteen references had been missed by the Cochrane's Centralised Search Service: six had PubMed-not-MEDLINE status, four were missed by the centralized Embase search, three had been misclassified by Cochrane Crowd, one was from a journal not indexed in MEDLINE or Embase, one had only been added to Embase in 2019, and one reference had been rejected by the automated RCT machine learning classifier. Of the sixteen missed references, eight were the main or only publication to the trial in the review in which it had been included.Conclusion: This analysis has shown that Cochrane's centralized search and screening processes are highly sensitive. It has also helped us to understand better why some references to eligible RCTs have been missed. The CSS is playing a critical role in helping to populate CENTRAL and is moving us toward making CENTRAL a comprehensive repository of RCTs. (c) 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4. 0/).