Testing moderation in network meta-analysis with individual participant data

Getachew A. Dagne*, C. Hendricks Brown, George Howe, Sheppard G. Kellam, Lei Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Meta-analytic methods for combining data from multiple intervention trials are commonly used to estimate the effectiveness of an intervention. They can also be extended to study comparative effectiveness, testing which of several alternative interventions is expected to have the strongest effect. This often requires network meta-analysis (NMA), which combines trials involving direct comparison of two interventions within the same trial and indirect comparisons across trials. In this paper, we extend existing network methods for main effects to examining moderator effects, allowing for tests of whether intervention effects vary for different populations or when employed in different contexts. In addition, we study how the use of individual participant data may increase the sensitivity of NMA for detecting moderator effects, as compared with aggregate data NMA that employs study-level effect sizes in a meta-regression framework. A new NMA diagram is proposed. We also develop a generalized multilevel model for NMA that takes into account within-trial and between-trial heterogeneity and can include participant-level covariates. Within this framework, we present definitions of homogeneity and consistency across trials. A simulation study based on this model is used to assess effects on power to detect both main and moderator effects. Results show that power to detect moderation is substantially greater when applied to individual participant data as compared with study-level effects. We illustrate the use of this method by applying it to data from a classroom-based randomized study that involved two sub-trials, each comparing interventions that were contrasted with separate control groups.

Original languageEnglish (US)
Pages (from-to)2485-2502
Number of pages18
JournalStatistics in Medicine
Volume35
Issue number15
DOIs
StatePublished - Jul 10 2016

Keywords

  • Integrative data analysis
  • Meta-analysis
  • Moderation
  • Network meta-analysis
  • Participant level data
  • Statistical power

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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