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Degree irregularity and rank probability bias in network meta-analysis
Annabel L Davies1, Tobias Galla1,2
1Theoretical Physics, Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester, Manchester, UK.
Research Synthesis Methods
|September 16, 2020
Summary
Network meta-analysis (NMA) uses network topology to compare treatments. Irregular networks introduce bias in treatment rankings and reduce precision, highlighting the need for balanced study designs in NMA.
Area of Science:
- Biostatistics
- Medical Informatics
- Complex Systems Analysis
Background:
- Network meta-analysis (NMA) is a statistical method for comparing multiple treatments.
- NMA outcomes include treatment effect estimates and rank probabilities.
- The impact of network topology on NMA accuracy and precision is not fully understood.
Purpose of the Study:
- To investigate how network topology, specifically the distribution of trials across treatments, affects NMA outcomes.
- To quantify the relationship between network structure and the reliability of NMA results.
Main Methods:
- A simulation study was conducted to analyze Bayesian Network Meta-Analysis (NMA).
- A novel metric, "degree irregularity," was defined to quantify asymmetry in study distribution within the network.
- Simulations explored the effects of varying network topologies on treatment effect estimates and rank probabilities.
Main Results:
- Disparity in trial numbers across treatments introduces systematic bias in estimated rank probabilities.
- Higher network "degree regularity" correlates with more precise treatment effect estimates and reduced rank probability bias.
- Topological effects did not significantly impact the accuracy of treatment effect estimates.
Conclusions:
- Network degree regularity is a crucial indicator of NMA parameter estimate accuracy and precision, outperforming total study counts or trial disparity metrics.
- Network topology significantly influences NMA reliability, necessitating consideration in study design.
- Future trial planning should aim to reduce network irregularity to enhance NMA precision and accuracy.
Keywords:
network meta-analysisnetwork topology and degree irregularityplanning future trialsrank probabilitysimulation studyMore Related Videos
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