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Evidence inconsistency degrees of freedom in Bayesian network meta-analysis

Lifeng Lin1

  • 1Department of Statistics, Florida State University, Tallahassee, Florida, USA.

Journal of Biopharmaceutical Statistics
|December 9, 2020
PubMed

Insights

New inconsistency degrees of freedom (ICDF) measures effectively assess network meta-analysis (NMA) validity, even with complex multi-arm studies. These novel methods improve upon existing measures, offering interpretable results across diverse NMA scenarios.

Area of Science:

  • Biostatistics
  • Health Research Methodology
  • Evidence Synthesis

Background:

  • Network meta-analysis (NMA) synthesizes evidence from multiple treatments.
  • Evidence inconsistency poses a significant threat to NMA validity.
  • Existing inconsistency degrees of freedom (ICDF) measures struggle with multi-arm studies.

Purpose of the Study:

  • To propose novel ICDF measures for NMAs, particularly those including multi-arm studies.
  • To enhance the assessment of evidence inconsistency in complex NMA settings.

Main Methods:

  • Developed new ICDF measures based on the effective number of parameters in Bayesian hierarchical models.
  • Compared proposed measures against existing ones using artificial and empirical NMAs.
  • Evaluated performance in both fixed- and random-effects models.

Main Results:

  • The proposed fixed-effects ICDF measure closely matched the existing measure in two-arm study-only NMAs.
  • 27 out of 39 (69%) empirical NMAs contained multi-arm studies, rendering existing measures inapplicable.
  • The new ICDF measures provided interpretable results for all tested NMAs, including those with multi-arm studies.

Conclusions:

  • The proposed ICDF measures are applicable and effective for NMAs with multi-arm studies.
  • These new measures enhance the reliability of evidence synthesis by addressing limitations in inconsistency assessment.
  • The findings support the adoption of these improved ICDF measures in NMA practice.
Keywords:
Bayesian analysisdirect evidenceeffective number of parametersevidence inconsistencyindirect evidencenetwork meta-analysis

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