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Overlapping network meta-analyses on the same topic: survey of published studies.
F Naudet1, E Schuit1,2, J P A Ioannidis1,3
1Meta-Research Innovation Center at Stanford, Stanford University, Stanford, CA, USA.
International Journal of Epidemiology
|October 18, 2017
Summary
Most published network meta-analyses (NMAs) have overlapping counterparts, indicating potential redundancy. This overlap in comparative effectiveness research may stem from inconsistent trial selection and intervention definitions, causing confusion.
Area of Science:
- Health Research Methodology
- Biostatistics
- Evidence Synthesis
Background:
- Network meta-analyses (NMAs) are increasingly used to synthesize evidence on comparative effectiveness.
- The frequency and extent of overlap between published NMAs are not well understood.
- Overlapping studies may lead to redundancy and potential inconsistencies in evidence synthesis.
Purpose of the Study:
- To determine the prevalence of overlapping network meta-analyses (NMAs) for the same health interventions.
- To evaluate the degree of overlap in terms of study components (nodes, treatments, references).
Main Methods:
- A random sample of 88 NMAs of randomized controlled trials was selected.
- Each index NMA was searched for overlapping NMAs on the same topic.
- A subset of 40 overlapping NMA pairs was analyzed for shared nodes, treatments, and references.
Main Results:
- A significant proportion (77%) of the index NMAs had at least one overlapping NMA.
- A total of 515 pairs of overlapping NMAs were identified.
- Substantial overlap was observed in nodes (73%), treatments (79%), and references (48%) among selected pairs.
- The efficacy of biologics in rheumatoid arthritis was the most common topic with 28 overlapping NMAs.
Conclusions:
- Published NMAs frequently exhibit considerable overlap and potential redundancy.
- Inconsistencies in trial retrieval, intervention selection, and node definition contribute to varying network structures and findings.
- This overlap can lead to confusion in interpreting comparative effectiveness research.
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