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Modeling the Functional Network for Spatial Navigation in the Human Brain

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Model selection for component network meta-analysis in connected and disconnected networks: a simulation study.

Maria Petropoulou¹, Gerta Rücker¹, Stephanie Weibel²

¹Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Stefan-Meier-Straße 26, 79104, Freiburg, Germany.

BMC Medical Research Methodology

|June 14, 2023

Summary

This summary is machine-generated.

Component network meta-analysis (CNMA) can effectively analyze interventions in connected networks. However, its use in disconnected networks is questionable, especially without strong evidence for additive component effects.

Keywords:

Component network meta-analysis Disconnected networks Model selection Multicomponent interventions Simulation

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Area of Science:

Biostatistics
Clinical Epidemiology
Health Services Research

Background:

Network meta-analysis (NMA) estimates and ranks intervention effects.
Component network meta-analysis (CNMA) extends NMA by analyzing individual components of multicomponent interventions.
CNMA can reconnect disconnected networks using common components and allows relaxing additivity assumptions.

Purpose of the Study:

To evaluate a forward model selection strategy for CNMA to relax additivity assumptions in connected and disconnected networks.
To describe a procedure for creating disconnected networks to assess model selection properties.
To apply and compare CNMA methods using simulated data and a real-world clinical review.

Main Methods:

Utilized a forward model selection strategy for CNMA.
Developed a procedure to generate disconnected networks for evaluation.
Applied methods to simulated data and a Cochrane review on postoperative nausea and vomiting interventions.
Assessed model performance using average mean squared errors and coverage probabilities.

Main Results:

CNMA models demonstrated good performance in connected networks, serving as an alternative to standard NMA when additivity is appropriate.
For disconnected networks, the additive CNMA is recommended only when strong clinical evidence supports additivity.
Model selection strategies were evaluated for their effectiveness in various network structures.

Conclusions:

Component network meta-analysis (CNMA) is a feasible method for connected networks.
The application of CNMA in disconnected networks requires careful consideration and is generally questionable.
Additive CNMA in disconnected networks should only be used with robust clinical justification.