There are often multiple potential interventions to treat a disease; therefore, we need a method for simultaneously comparing and ranking all of these available interventions. In contrast to pairwise meta-analysis, which allows for the comparison of one intervention to another based on head-to-head data from randomized trials, network meta-analysis (NMA) facilitates simultaneous comparison of the efficacy or safety of multiple interventions that may not have been directly compared in a randomized trial. NMAs help researchers study important and previously unanswerable questions, which have contributed to a rapid rise in the number of NMA publications in the biomedical literature. However, the conduct and interpretation of NMAs are more complex than pairwise meta-analyses: there are additional NMA model assumptions (i.e., network connectivity, homogeneity, transitivity, and consistency) and outputs (e.g., network plots and surface under the cumulative ranking curves [SUCRAs]). In this chapter, we will: (1) explore similarities and differences between pairwise and network meta-analysis; (2) explain the differences between direct, indirect, and mixed treatment comparisons; (3) describe how treatment effects are derived from NMA models; (4) discuss key criteria predicating completion of NMA; (5) interpret NMA outputs; (6) discuss areas of ongoing methodological research in NMA; (7) outline an approach to conducting a systematic review and NMA; (8) describe common problems that researchers encounter when conducting NMAs and potential solutions; and (9) outline an approach to critically appraising a systematic review and NMA.

Network Meta-Analysis / Watt, J.; Del Giovane, C.. - 2345:(2022), pp. 187-201. [10.1007/978-1-0716-1566-9_12]

Network Meta-Analysis

Del Giovane C.
2022-01-01

Abstract

There are often multiple potential interventions to treat a disease; therefore, we need a method for simultaneously comparing and ranking all of these available interventions. In contrast to pairwise meta-analysis, which allows for the comparison of one intervention to another based on head-to-head data from randomized trials, network meta-analysis (NMA) facilitates simultaneous comparison of the efficacy or safety of multiple interventions that may not have been directly compared in a randomized trial. NMAs help researchers study important and previously unanswerable questions, which have contributed to a rapid rise in the number of NMA publications in the biomedical literature. However, the conduct and interpretation of NMAs are more complex than pairwise meta-analyses: there are additional NMA model assumptions (i.e., network connectivity, homogeneity, transitivity, and consistency) and outputs (e.g., network plots and surface under the cumulative ranking curves [SUCRAs]). In this chapter, we will: (1) explore similarities and differences between pairwise and network meta-analysis; (2) explain the differences between direct, indirect, and mixed treatment comparisons; (3) describe how treatment effects are derived from NMA models; (4) discuss key criteria predicating completion of NMA; (5) interpret NMA outputs; (6) discuss areas of ongoing methodological research in NMA; (7) outline an approach to conducting a systematic review and NMA; (8) describe common problems that researchers encounter when conducting NMAs and potential solutions; and (9) outline an approach to critically appraising a systematic review and NMA.
2022
Methods in Molecular Biology
978-1-0716-1565-2
978-1-0716-1566-9
Humana Press Inc.
Network Meta-Analysis / Watt, J.; Del Giovane, C.. - 2345:(2022), pp. 187-201. [10.1007/978-1-0716-1566-9_12]
Watt, J.; Del Giovane, C.
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