A Novel Visualisation for Assessing the Consistency Assumption in Network Meta-Analysis

Author(s)

Wilson H1, Schoenstein A2, Bonofiglio F3
1Veramed Ltd, London, UK, 2Veramed GmbH, Mannheim, Germany, 3Veramed GmbH, Freiburg, Germany

Presentation Documents

OBJECTIVES: Network meta-analysis (NMA) is the established method to pool evidence from multiple clinical trials and make direct and indirect comparisons between different treatments. However, to ensure its validity, several assumptions need to be examined. Chief among these is the assumption that the different sources of information are consistent, which is to say that the direct and indirect effect estimates agree. There are at least three different aspects to consider: (1) the original effect sizes of the direct and indirect treatment effects; (2) the difference between them and its associated uncertainty; and (3) the type of difference between them i.e., whether the direct and indirect estimates agree that a treatment is beneficial or harmful. Current visualisation approaches typically use forest plots, but these are limited as at least one of the above aspects is usually absent to avoid introducing excessive complexity. Furthermore, as the number of treatments in the network increases, these visualisations can become difficult to understand. Hence, a visualisation that combines the three aspects without being too complex or difficult to interpret would allow for a more thorough examination of the assumption.

METHODS: We propose a new type of visualisation that integrates the forest plots that are currently used with a scatter graph of the direct effects against the indirect effects. The distance of the points from the y = x line can then be used to represent the difference (and its uncertainty) between the direct and indirect effects. The four quadrants of the graph also allow the type of difference to be inferred.

RESULTS: The proposed visualisation provides a concise and intuitive solution to the problem and allows the assumption to be effectively assessed.

CONCLUSIONS: The visualisation offers an improvement on current visualisation strategies, but further research is required to properly assess its efficacy and practicality.

Conference/Value in Health Info

2023-05, ISPOR 2023, Boston, MA, USA

Value in Health, Volume 26, Issue 6, S2 (June 2023)

Code

MSR89

Topic

Study Approaches

Topic Subcategory

Meta-Analysis & Indirect Comparisons

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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