Abstract
Network meta-analysis (NMA) is used to synthesise results from multiple treatments where the RCTs form a connected network of treatments. It provides a framework for comparative effectiveness and assessment of consistency between the direct and indirect evidence and is extensively employed in health economic modelling to inform healthcare policy. Multiple doses of different agents in an NMA are typically ""split"" or ""lumped"". Splitting involves modelling different doses of an agent as independent nodes in the network, making no assumptions regarding how they are related, and can results in sparse or even disconnected networks in which NMA is impossible. Lumping assumes different doses have the same efficacy, which can introduce heterogeneity or inconsistency. MBNMAdose is an R package that allows dose-response relationships to be explicitly modelled using Model-Based NMA (MBNMA). As well as avoiding problems arising from lumping/splitting, this modelling framework can improve precision of estimates over those estimated using standard NMA, allow for interpolation/extrapolation of predicted responses based on the dose-response relationship, and allow for the linking of disconnected networks via the dose-response relationship. MBNMAdose provides a suite of functions that make it easy to implement Bayesian MBNMA models, evaluate their suitability given the data, and produce meaningful outputs from the analyses that can be used in decision-making.
Original language | English |
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DOIs | |
Publication status | Unpublished - 21 Jan 2021 |
Event | Evidence Synthesis and Meta-Analysis in R Conference 2021 - Online Duration: 21 Jan 2021 → 22 Jan 2021 https://www.eshackathon.org/events/2021-01-ESMAR.html |
Conference
Conference | Evidence Synthesis and Meta-Analysis in R Conference 2021 |
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Abbreviated title | ESMARConf 2021 |
Period | 21/01/21 → 22/01/21 |
Internet address |
Keywords
- dose-response
- meta-analysis
- Bayesian Analysis
- Network Meta-Analysis
- software