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Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a

Lauren McKeen1, Paul Morris1, Chong Wang2,3

  • 1Department of Statistics, Iowa State University, Ames, USA.

BMC Medical Research Methodology
|April 4, 2023
PubMed
Abstract

Insights

This study introduces a method to identify the optimal connecting trial for disconnected networks in meta-analysis. This approach minimizes variation in treatment effect estimation, potentially favoring indirect connections.

Area of Science:

  • Biostatistics
  • Epidemiology
  • Health Research Methodology

Background:

  • Network meta-analysis enables comparative effect estimation for directly or indirectly connected treatments.
  • Disconnected trial networks present challenges for comprehensive treatment comparisons, often requiring strong assumptions in existing models.
  • New trials can bridge disconnected networks, maximizing the value of existing data.

Purpose of the Study:

  • To develop an approach for identifying the optimal connecting trial in a disconnected network meta-analysis.
  • To provide a method for researchers to maximize the value of existing trial networks.

Main Methods:

  • Formulas were developed to quantify the variation in estimating a specific comparative effect for any potential two-arm connecting trial.
  • A procedure was proposed to identify the optimal connecting trial that minimizes this estimation variation.

Main Results:

  • Connecting treatments indirectly can be more advantageous than direct connection via a new trial, by utilizing existing disconnected network information.
  • A real-world network of vaccines for bovine respiratory disease (BRD) was used to illustrate the procedure.
  • Findings were confirmed through simulation studies.

Conclusions:

  • The provided procedure aids researchers in selecting the best connecting two-arm study.
  • The optimal connecting trial is network-dependent, and indirect connections may be preferable to direct ones.
Keywords:
Clinical trial designEvidence synthesisNetwork meta-analysis

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