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Network meta-analysis of multicomponent interventions.

Gerta Rücker1, Maria Petropoulou2, Guido Schwarzer1

  • 1Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Biometrical Journal. Biometrische Zeitschrift
|April 26, 2019
PubMed
Summary
This summary is machine-generated.

Component network meta-analysis (CNMA) models offer a novel approach to analyzing complex treatments by leveraging shared components. This method, implemented in the R package netmeta, enhances network meta-analysis for better insights.

Keywords:
combination therapiescomplex interventionsdisconnected networksmultiple interventionsnetwork meta-analysis

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Area of Science:

  • Statistics
  • Medical Informatics
  • Pharmacology

Background:

  • Standard network meta-analysis (NMA) treats all treatments as distinct nodes.
  • Complex interventions, often combinations of components, present analytical challenges in NMA.
  • Component network meta-analysis (CNMA) models utilize shared components within treatments.

Purpose of the Study:

  • To implement and describe component network meta-analysis (CNMA) models.
  • To demonstrate the application of CNMA models in a frequentist framework using the R package netmeta.
  • To explore the utility of CNMA models in complex and disconnected networks.

Main Methods:

  • Development of additive and interaction CNMA models.
  • Implementation of CNMA models using weighted least squares regression in the netmeta R package.
  • Application of CNMA models to a network meta-analysis of depression treatments in primary care.

Main Results:

  • The netmeta package now supports frequentist CNMA models.
  • CNMA models can effectively analyze treatments composed of common components.
  • The models are applicable even to disconnected networks with common components.

Conclusions:

  • CNMA models provide a valuable alternative for analyzing complex interventions in network meta-analysis.
  • The frequentist implementation in netmeta facilitates broader application of CNMA.
  • CNMA enhances the ability to analyze treatment effects by accounting for component interactions and additive effects.