Multivariate network meta-analysis incorporating class effects.

ABSTRACT:

Background

Network meta-analysis synthesises data from a number of clinical trials in order to assess the comparative efficacy of multiple healthcare interventions in similar patient populations. In situations where clinical trial data are heterogeneously reported i.e. data are missing for one or more outcomes of interest, synthesising such data can lead to disconnected networks of evidence, increased uncertainty, and potentially biased estimates which can have severe implications for decision-making. To overcome this issue, strength can be borrowed between outcomes of interest in multivariate network meta-analyses. Furthermore, in situations where there are relatively few trials informing each treatment comparison, there is a potential issue with the sparsity of data in the treatm

SUBMITTER: Owen RK 

PROVIDER: S-EPMC7341581 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature