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Methodological Standards for Meta-Analyses and Qualitative Systematic Reviews of Cardiac Prevention and Treatment Studies: A Scientific Statement From the American Heart Association

Authors :
Katherine Kirley
Christopher Masi
Frank D'Amico
Tiffany M. Powell-Wiley
Anthony Solomonides
Goutham Rao
Jennifer Wessel
Jack H. Boyd
Francisco Lopez-Jimenez
Nefertiti Durant
George Howard
Colin P. West
Mark A. Hlatky
Source :
Circulation. 136
Publication Year :
2017
Publisher :
Ovid Technologies (Wolters Kluwer Health), 2017.

Abstract

Meta-analyses are becoming increasingly popular, especially in the fields of cardiovascular disease prevention and treatment. They are often considered to be a reliable source of evidence for making healthcare decisions. Unfortunately, problems among meta-analyses such as the misapplication and misinterpretation of statistical methods and tests are long-standing and widespread. The purposes of this statement are to review key steps in the development of a meta-analysis and to provide recommendations that will be useful for carrying out meta-analyses and for readers and journal editors, who must interpret the findings and gauge methodological quality. To make the statement practical and accessible, detailed descriptions of statistical methods have been omitted. Based on a survey of cardiovascular meta-analyses, published literature on methodology, expert consultation, and consensus among the writing group, key recommendations are provided. Recommendations reinforce several current practices, including protocol registration; comprehensive search strategies; methods for data extraction and abstraction; methods for identifying, measuring, and dealing with heterogeneity; and statistical methods for pooling results. Other practices should be discontinued, including the use of levels of evidence and evidence hierarchies to gauge the value and impact of different study designs (including meta-analyses) and the use of structured tools to assess the quality of studies to be included in a meta-analysis. We also recommend choosing a pooling model for conventional meta-analyses (fixed effect or random effects) on the basis of clinical and methodological similarities among studies to be included, rather than the results of a test for statistical heterogeneity.

Details

ISSN :
15244539 and 00097322
Volume :
136
Database :
OpenAIRE
Journal :
Circulation
Accession number :
edsair.doi.dedup.....02a1546199b04af83255e49fd4815422
Full Text :
https://doi.org/10.1161/cir.0000000000000523