Measuring inconsistency in meta-analyses
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TLDR
A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.Abstract:
Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?
Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis.
Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4
Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted?
A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …read more
Citations
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Systematic review and meta-analysis
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Alessandro Liberati,Douglas G. Altman,Jennifer Tetzlaff,Cynthia D. Mulrow,Peter C Gøtzsche,John P. A. Ioannidis,Mike Clarke,Mike Clarke,Philip J. Devereaux,Jos Kleijnen,David Moher +10 more
TL;DR: An Explanation and Elaboration of the PRISMA Statement is presented and updated guidelines for the reporting of systematic reviews and meta-analyses are presented.
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The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration
Alessandro Liberati,Douglas G. Altman,Jennifer Tetzlaff,Cynthia D. Mulrow,Peter C Gøtzsche,John P. A. Ioannidis,Mike Clarke,Philip J. Devereaux,Jos Kleijnen,David Moher +9 more
TL;DR: The meaning and rationale for each checklist item is explained, and an example of good reporting is included and, where possible, references to relevant empirical studies and methodological literature are included.
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Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation.
Larissa Shamseer,David Moher,Mike Clarke,Davina Ghersi,Alessandro Liberati,Mark Petticrew,Paul G. Shekelle,Lesley A. Stewart +7 more
TL;DR: The PRISMA-P checklist as mentioned in this paper provides 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol, as well as a model example from an existing published protocol.
Journal ArticleDOI
The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration
Alessandro Liberati,Douglas G. Altman,Jennifer Tetzlaff,Cynthia D. Mulrow,Peter C Gøtzsche,John P. A. Ioannidis,Mike Clarke,Mike Clarke,Philip J. Devereaux,Jos Kleijnen,David Moher +10 more
TL;DR: This Explanation and Elaboration document explains the meaning and rationale for each checklist item and includes an example of good reporting and, where possible, references to relevant empirical studies and methodological literature.
References
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Journal ArticleDOI
Heterogeneity and statistical significance in meta-analysis: an empirical study of 125 meta-analyses.
TL;DR: This work studied 125 meta-analyses representative of those performed by clinical investigators to examine empirically how assessment of treatment effect and heterogeneity may differ when different methods are utilized, and presents two exceptions to these observations.
Journal ArticleDOI
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TL;DR: By simulation, small sample performance in terms of size of ten procedures for testing the homogeneity of odds ratios in K 2 x 2 contingency tables is studied.