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Introduction to Meta-Analysis

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Principles and Practice of Clinical Trials

Abstract

Studies within a systematic review are often combined statistically in a meta-analysis, which quantitatively synthesizes all available evidence about the relative effects of two healthcare interventions for the same clinical outcome. A key issue in every meta-analysis is whether the identified randomized control trials (RCTs) are similar enough to be combined together since important differences in trial- or patient-level characteristics may affect the treatment effects. Such differences, called heterogeneity, need to be properly investigated and accounted for in the analysis. In this chapter, we introduce the basic concepts of meta-analyses of RCTs and we describe the two main meta-analytical models, namely, the common effect and the random effects models. Then, we present several ways to identify and assess heterogeneity. We discuss the interpretation of results from a meta-analysis using two exemplar datasets. The chapter closes with a brief introduction to more sophisticated meta-analytical techniques such as the use of individual participant data and network meta-analysis.

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Correspondence to Anna Chaimani .

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Evrenoglou, T., Metelli, S., Chaimani, A. (2021). Introduction to Meta-Analysis. In: Piantadosi, S., Meinert, C.L. (eds) Principles and Practice of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-52677-5_287-1

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  • DOI: https://doi.org/10.1007/978-3-319-52677-5_287-1

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  • Print ISBN: 978-3-319-52677-5

  • Online ISBN: 978-3-319-52677-5

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