Using the contribution matrix to evaluate complex study limitations in a network meta-analysis: a case study of bipolar maintenance pharmacotherapy review.

Abstract

BACKGROUND:

Limitations in the primary studies constitute one important factor to be considered in the grading of recommendations assessment, development, and evaluation (GRADE) system of rating quality of evidence. However, in the network meta-analysis (NMA), such evaluation poses a special challenge because each network estimate receives different amounts of contributions from various studies via direct as well as indirect routes and because some biases have directions whose repercussion in the network can be complicated.

FINDINGS:

In this report we use the NMA of maintenance pharmacotherapy of bipolar disorder (17 interventions, 33 studies) and demonstrate how to quantitatively evaluate the impact of study limitations using netweight, a STATA command for NMA. For each network estimate, the percentage of contributions from direct comparisons at high, moderate or low risk of bias were quantified, respectively. This method has proven flexible enough to accommodate complex biases with direction, such as the one due to the enrichment design seen in some trials of bipolar maintenance pharmacotherapy.

CONCLUSIONS:

Using netweight, therefore, we can evaluate in a transparent and quantitative manner how study limitations of individual studies in the NMA impact on the quality of evidence of each network estimate, even when such limitations have clear directions.

• Authors: Toshi A Furukawa, Tomofumi Miura, Anna Chaimani, Stefan Leucht, Andrea Cipriani, Hisashi Noma, Hiroshi Mitsuyasu, Shegenobu Kanba, Georgia Salanti
• Journal: BMC research notes (BMC Res Notes) Vol. 9 Pg. 218 (Apr 14 2016) ISSN: 1756-0500 [Electronic] England
• PMID: 27074861 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Topics

• Algorithms
• Bias
• Bipolar Disorder (drug therapy)
• Humans
• Maintenance Chemotherapy (methods)
• Models, Theoretical
• Network Meta-Analysis
• Review Literature as Topic