ESMARConf2022 Special Session 4: Quantitative synthesis - NMA - Tasnim Hamza
Channel: ESMARConf
Date: 23/02/2022

Presenter: Tasnim Hamza
Session: Special Session 4: Quantitative synthesis - NMA
Title: crossnma:  A new R package to synthesize cross-design evidence and cross-format data
Abstract: Network meta-analysis (NMA) is commonly used to compare between interventions simultaneously by synthesising the available evidence. That evidence is obtained either from non-randomized studies (NRS) or randomized controlled trials and is accessible as individual participant data (IPD) or aggregate data (AD). We have developed a new R package, crossnma, which allows us to combine these different pieces of information while accounting for their differences. The package conducts a Bayesian NMA and meta-regression to synthesize cross-design evidence and cross-format data. It runs a range of models with JAGS by generating the code automatically from user’s input. A three-levels hierarchical model is implemented to combine IPD and AD and we also integrate four different models for combining the different study designs (a) ignoring their differences in risk of bias (b) using NRS to construct discounted treatment effect priors (c,d) adjusting for the risk of bias in each study in two different ways. Up to three study- or patient-level covariates can also be included, which may help explaining some of the heterogeneity and inconsistency across trials. TH and GS are supported by the HTx-project. The HTx project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 825162.

Please cite as: Hamza, Tasnim (2022) crossnma:  A new R package to synthesize cross-design evidence and cross-format data. ESMARConf2022 conference presentation. Zenodo. https://doi.org/10.5281/zenodo.6076316