Double-counting of populations in evidence synthesis in public health: a call for awareness and future methodological development.
Double-counting of populations in evidence synthesis in public health: a call for awareness and future methodological development.
复制标题
DOI：
10.1186/s12889-022-14213-6
复制
发表时间：
2022-09-27
影响因子：
4.5
通讯作者：
中科院分区：
文献类型：
--
作者：
人们越来越关注将真实世界和观察性研究纳入证据合成，如公共卫生中的荟萃分析和网络荟萃分析。虽然这一方法提供了很大的流行病学机会，但使用这类研究往往会带来一个重大问题，即在一次分析中重复计算参与者和数据库。因此，本研究旨在介绍和说明证据合成中重复计算个体的细微差别，包括真实世界和观察数据，重点是公共卫生。与证据合成中的个人重复计算相关的问题突出了一些案例研究。此外，重复计算的信息在不同的情况下进行了讨论，突出了潜在的解决方案。使用真实世界数据的研究和/或已建立的队列研究，例如使用健康记录数据评估治疗有效性的研究，通常会引入重复计算个人和数据库的重要问题。这是指在一次分析中多次纳入相同的个体。重复计算可能以多种方式发生，例如，当多项研究使用相同的数据库时，当研究之间存在重叠的分析时间范围或共同的治疗组时。解决这一问题的一些常见做法包括仅从同行评审研究中综合数据，利用提供最大信息的研究（例如报告的最大，最新，更大的结果）或分析不同时间点的结果。虽然目前使用的通用做法可以减轻证据合成（包括真实世界和观察性研究）中重复计算参与者的影响，但显然需要制定方法和指南，以解决这一日益重要的问题。
There is a growing interest in the inclusion of real-world and observational studies in evidence synthesis such as meta-analysis and network meta-analysis in public health. While this approach offers great epidemiological opportunities, use of such studies often introduce a significant issue of double-counting of participants and databases in a single analysis. Therefore, this study aims to introduce and illustrate the nuances of double-counting of individuals in evidence synthesis including real-world and observational data with a focus on public health. The issues associated with double-counting of individuals in evidence synthesis are highlighted with a number of case studies. Further, double-counting of information in varying scenarios is discussed with potential solutions highlighted. Use of studies of real-world data and/or established cohort studies, for example studies evaluating the effectiveness of therapies using health record data, often introduce a significant issue of double-counting of individuals and databases. This refers to the inclusion of the same individuals multiple times in a single analysis. Double-counting can occur in a number of manners, such as, when multiple studies utilise the same database, when there is overlapping timeframes of analysis or common treatment arms across studies. Some common practices to address this include synthesis of data only from peer-reviewed studies, utilising the study that provides the greatest information (e.g. largest, newest, greater outcomes reported) or analysing outcomes at different time points. While common practices currently used can mitigate some of the impact of double-counting of participants in evidence synthesis including real-world and observational studies, there is a clear need for methodological and guideline development to address this increasingly significant issue.
登录
查看更多内容
影响因子：
2.9
作者：
Meffen A;Houghton JSM;Nickinson ATO;Pepper CJ;Sayers RD;Gray LJ
通讯作者：
Gray LJ
DOI：
10.1136/bmj.e5798
发表时间：
2012-09-11
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Hutton B;Joseph L;Fergusson D;Mazer CD;Shapiro S;Tinmouth A
通讯作者：
Tinmouth A
影响因子：
9.3
作者：
Niedzwiedz, Claire L.;O'Donnell, Kate A.;Katikireddi, S. Vittal
通讯作者：
Katikireddi, S. Vittal
影响因子：
9.8
作者：
Paulus, Jessica K.;Dahabreh, Issa J.;Ip, Stanley
通讯作者：
Ip, Stanley
影响因子：
4
作者：
Mueller M;D'Addario M;Egger M;Cevallos M;Dekkers O;Mugglin C;Scott P
通讯作者：
Scott P