Article
Incorporation of Multiple Studies in Adjusted Indirect Comparisons
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Authors
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Dorothea Weber
- Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
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Katrin Jensen
- Universität Heidelberg, Heidelberg, Germany
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Meinhard Kieser
- Universität Heidelberg, Heidelberg, Germany
| Published: | February 26, 2021 |
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Outline
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Objective: In evidence synthesis, indirect comparisons are widely used to compare treatments where direct evidence is missing. However, methods for indirect comparisons showed bad performance in terms of power. The matching adjusted indirect comparison (MAIC) [1] procedure is designed for the use of one study per treatment comparison and when individual patient data (IPD) is available for only one comparison. However, in practice it is likely that more than one study is available for at least one comparison and using all available trials may enhance power and reduce bias of indirect comparisons.
Methods: We propose and compare approaches for incorporating multiple studies in indirect comparisons.
The MAIC with its matching step allows for different approaches to include several studies. The main difference is whether treatment effects or data is pooled before or after applying a method for indirect comparisons. For comparison, all proposed approaches are additionally applied to the method of Bucher [2]. The performance is evaluated by a simulation study covering practically relevant scenarios and a clinically motivated data set. The situation of a time-to-event endpoint is considered and differences in population characteristics as well as effect modification are taken into account.
Results: We observe a gain in power when using more than one trial per direct treatment comparison, which increases mainly with an increasing number of IPD trials. When population characteristics are equal or only one IPD trial is included, pooling treatment effects/data before performing the indirect comparison shows better performance. However, in case of different population distributions and presence of effect modification, conducting all indirect comparisons results in higher power and less biased treatment effects. Notwithstanding the applied method, results are often biased and need to be interpreted with caution.
The authors declare that they have no competing interests.
The authors declare that an ethics committee vote is not required.
References
- 1.
- Signorovitch JE, Sikirica V, Erder MH, et al. Matching-adjusted indirect comparisons: a new tool for timely comparative effectiveness research. Value Health. 2012;15(6):940-947. DOI: 10.1016/j.jval.2012.05.004
- 2.
- Bucher HC, et al. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol. 1997;50(6):683-691.
