Network meta-analysis is becoming increasingly important for decision makers to assess the comparative efficacy and safety of interventions and is integral to health technology assessment (HTA). The exploration of covariate effects is important in network meta-analysis (NMA) because the presence of unaccounted treatment covariate interactions can invalidate the assumptions which underlie NMA and bias results. Visually assimilating, exploring and interpreting the distribution of covariate values across trials in an NMA is challenging due to the complexities of representing the network structure simultaneously alongside study-level covariate values.

DRG abacus has developed a 3-dimensional (3-D) evidence network plot system - a novel, freely-accessible, web-based package in collaboration with leading academics at the University of Leicester. The 3-D evidence network plot system is the first tool designed specifically to visualize covariate distributions and imbalances across evidence networks in 3-D. The primary innovation within the tool which allows for the extensions to evidence networks and improvements is the use of a 3-D graphical environment, incorporating the graphical representation of covariates (continuous and aggregate patient-level dichotomous) on a third ‘z’ axis.

The tool will be of primary interest to systematic review and meta-analysis researchers, and, more generally, those assessing the validity and robustness of an NMA to inform reimbursement decisions. Full details of the rationale and feature of the software tool can be found in a recent publication in the journal of clinical epidemiology [1].

 

For further information on any aspects of SR and NMA or to request a demo of the tool please contact our in-house experts at Access@teamdrg.com

 

  1. Batson, S., R. Score, and A.J. Sutton, 3-D evidence network plot system: Covariate imbalances and effects in network meta-analysis explored using a new software tool. J Clin Epidemiol, 2017.

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