Volume 16, Issue 2 (7-2020)                   HSR 2020, 16(2): 143-150 | Back to browse issues page


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Ghasemi K, Mansourian M, Vaseghi G. Network Meta-analysis Application in Comparison of Clinical Trial Studies. HSR 2020; 16 (2) :143-150
URL: http://hsr.mui.ac.ir/article-1-1135-en.html
1- Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
2- Associate Professor, Department of Biostatistics and Epidemiology, School of Health , Isfahan University of Medical Sciences, Isfahan, Iran
3- Assistant Professor, Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
Abstract:   (2983 Views)
Background: Healthcare decisions should be based on evidence generally provided by randomized controlled trials (RCTs) comparing two or more interventions for a condition that affects the target population.
Methods: When more than one study is available, meta-analysis can be used to combine several intervention effects and obtain an overall estimate of that effect size in the target population. However, for most clinical conditions, there are more than two effective interventions. In such cases, it is not possible to perform multiple pairwise meta-analysis. Additionally, direct clinical trials may not be designed and implemented for all interventions.
Findings: Network meta-analysis (NMA) is a method for comparing multiple interventions simultaneously in a single study using a combination of direct and indirect evidence in a network of RCTs the results of which enable us to rank all the interventions in a coherent way.
Conclusion: The present study was designed to provide a basic explanation of the benefits of producing a direct and indirect evidence-based network, reviewing key assumptions in NMA, and explaining the stages of performing NMA. In addition, by using an example to evaluate the cardiac toxicity of different interventions to treat HER-2 positive breast cancer, the implementation and production steps of the meta-analysis network were presented.
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Type of Study: Research |
Received: 2020/09/5 | Accepted: 2020/07/5 | Published: 2020/07/5

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