Automating network meta‐analysis

  title={Automating network meta‐analysis},
  author={Gert van Valkenhoef and Guobing Lu and Bert O. de Brock and Hans L. Hillege and A. E. Ades and Nicky J Welton},
  journal={Research Synthesis Methods},
Mixed treatment comparison (MTC) (also called network meta‐analysis) is an extension of traditional meta‐analysis to allow the simultaneous pooling of data from clinical trials comparing more than two treatment options. Typically, MTCs are performed using general‐purpose Markov chain Monte Carlo software such as WinBUGS, requiring a model and data to be specified using a specific syntax. It would be preferable if, for the most common cases, both could be derived from a well‐structured data file… 

Network meta-analysis: development of a three-level hierarchical modeling approach incorporating dose-related constraints.

  • R. OwenD. TincelloR. Keith
  • Medicine
    Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
  • 2015

A Gentle Introduction to Bayesian Network Meta-Analysis Using an Automated R Package.

Several essential concepts of Bayesian network meta-analysis are discussed, including the assumptions of homogeneity and consistency, the fixed and random effects models, prior specification, and model fit evaluation strategies, while pointing out some issues and areas where researchers should use caution in the application of BNMA.

Bayesian meta‐analysis using SAS PROC BGLIMM

This paper demonstrates that the recently‐developed SAS procedure BGLIMM provides an intuitive and computationally efficient means for conducting Bayesian meta‐analysis in SAS, using a worked example of a smoking cessation NMA data set.

ADDIS: an automated way to do network meta-analysis

The purpose of this report is to introduce an automated way to perform network meta-analysis through ADDIS (Aggregate Data Drug Information System) to detect the heterogeneity among di erent trials comparing the same treatments and inconsistency between direct and indirect evidence.

GetReal in network meta‐analysis: a review of the methodology

This article presents a review of the relevant literature on NMA methodology aiming to pinpoint the developments that have appeared in the field.

Network Meta-Analysis Using R: A Review of Currently Available Automated Packages

This paper aims to introduce the reader to three R packages, namely, gemtc, pcnetmeta, and netmeta, which are freely available software tools implemented in R and demonstrates that each provides a useful set of tools, and combined provide users with nearly all functionality that might be desired when conducting a NMA.

Network meta-analysis: a technique to gather evidence from direct and indirect comparisons

A basic explanation of network meta-analysis conduction is provided, highlighting its risks and benefits for evidence-based practice, including information on statistical methods evolution, assumptions and steps for performing the analysis.

A generalized pairwise modelling framework for network meta-analysis

A generalized pairwise modelling (GPM) framework for network meta-analysis, so named as it is based on the repeated application of adjusted indirect comparisons, also known as the Bucher method is introduced.

Should Network Meta-analysis Become the Standard in Evidence-based Clinical Practice?

Issues suggest that because NMA is still in its infancy compared to HTHC, more research and guidance for its use are necessary before it can be claimed that NMA should become the standard for comparing treatment effectiveness.

Overview of Network Meta-analysis for a Rheumatologist

Network meta-analysis is an interesting method that provides useful information for use in by rheumatologists in decision-making because it provides greater flexibility that allows for the use of more complex models and can produce estimates of rank probabilities.



Combination of direct and indirect evidence in mixed treatment comparisons

A range of Bayesian hierarchical models using the Markov chain Monte Carlo software WinBUGS are presented that allow for variation in true treatment effects across trials, and models where the between-trials variance is homogeneous across treatment comparisons are considered.

Meta‐analysis of mixed treatment comparisons at multiple follow‐up times

This work extends mixed treatment comparisons to a more complex situation where trials report results at one or more, different yet fixed, follow-up times and develops a series of Bayesian hierarchical models based on piece-wise exponential hazards that have a very wide potential application.

Algorithmic parameterization of mixed treatment comparisons

This paper defines the parameterization problem for inconsistency models in mathematical terms and provides an algorithm for the generation of inconsistency models and evaluates running-time of the algorithm by generating models for 15 published evidence structures.

Assessing Evidence Inconsistency in Mixed Treatment Comparisons

A general method for assessing evidence inconsistency in the framework of Bayesian hierarchical models, which represents evidence consistency as a set of linear relations between effect parameters on the log odds ratio scale, and relax these relations to allow for inconsistency by adding to the model random inconsistency factors (ICFs).

Meta-analysis: formulating, evaluating, combining, and reporting.

This article presents a tutorial on meta-analysis intended for anyone with a mathematical statistics background, focused on analytic methods for estimation of the parameters of interest.

A case study of multiple-treatments meta-analysis demonstrates that covariates should be considered.

Evaluation of networks of randomized trials

The concept of inconsistency and methods that have been proposed to evaluate it as well as the methodological gaps that remain are discussed and the implications of inconsistency, network geometry and asymmetry in informing the planning of future trials are discussed.

Modeling between-trial variance structure in mixed treatment comparisons.

This work starts from a consistent Bayesian hierarchical model for the mean treatment effects and represents the variance configuration by a set of triangle inequalities on the standard deviations, which allows incorporation of prior beliefs about the correlations between treatment effects.

Network meta‐analysis for indirect treatment comparisons

  • T. Lumley
  • Psychology, Environmental Science
    Statistics in medicine
  • 2002
I present methods for assessing the relative effectiveness of two treatments when they have not been compared directly in a randomized trial but have each been compared to other treatments. These

Fixed- and random-effects models in meta-analysis.

There are 2 families of statistical procedures in meta-analysis: fixed- and randomeffects procedures. They were developed for somewhat different inference goals: making inferences about the effect