Abstract
Objectives
Ranking metrics in network meta-analysis (NMA) are computed separately for each outcome.
Our aim is to 1) present graphical ways to group competing interventions considering
multiple outcomes and 2) use conjoint analysis for placing weights on the various
outcomes based on the stakeholders’ preferences.
Study Design and Setting
We used multidimensional scaling (MDS) and hierarchical tree clustering to visualize
the extent of similarity of interventions in terms of the relative effects they produce
through a random effect NMA. We reanalyzed a published network of 212 psychosis trials
taking three outcomes into account as follows: reduction in symptoms of schizophrenia,
all-cause treatment discontinuation, and weight gain.
Results
Conjoint analysis provides a mathematical method to transform judgements into weights
that can be subsequently used to visually represent interventions on a two-dimensional
plane or through a dendrogram. These plots provide insightful information about the
clustering of interventions.
Conclusion
Grouping interventions can help decision makers not only to identify the optimal ones
in terms of benefit-risk balance but also choose one from the best cluster based on
other grounds, such as cost, implementation etc. Placing weights on outcomes allows
considering patient profile or preferences.
Keywords
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Article info
Publication history
Published online: December 26, 2022
Accepted:
December 22,
2022
Footnotes
Author statement: Dimitris Mavridis: Conceptualization, Methodology, Software, Writing–Original draft preparation. Adriani Nikolakopoulou: Methodology, Validation, Writing–Reviewing and Editing. Irini Moustaki: Methodology, Writing–Reviewing and Editing. Anna Chaimani: Methodology, Writing–Reviewing and Editing. Raphaël Porcher: Methodology, Writing–Reviewing and Editing. Isabelle Boutron: Supervision, Writing–Reviewing and Editing. Philippe Ravaud: Supervision, Writing–Reviewing and Editing.
Declarations of interest: None.
Identification
Copyright
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