Issues in performing a network meta-analysis

Stephen Senn; Francois Gavini; David Magrez; André Scheen

doi:10.1177/0962280211432220

Issues in performing a network meta-analysis

Stephen Senn^*, Francois Gavini, David Magrez, André Scheen

^*Corresponding author for this work

Research output: Contribution to journal › Article › Research › peer-review

55 Citations (Scopus)

Abstract

The example of the analysis of a collection of trials in diabetes consisting of a sparsely connected network of 10 treatments is used to make some points about approaches to analysis. In particular various graphical and tabular presentations, both of the network and of the results are provided and the connection to the literature of incomplete blocks is made. It is clear from this example that is inappropriate to treat the main effect of trial as random and the implications of this for analysis are discussed. It is also argued that the generalisation from a classic random-effect meta-analysis to one applied to a network usually involves strong assumptions about the variance components involved. Despite this, it is concluded that such an analysis can be a useful way of exploring a set of trials.

Original language	English
Pages (from-to)	169-189
Number of pages	21
Journal	Statistical Methods in Medical Research
Volume	22
Issue number	2
DOIs	https://doi.org/10.1177/0962280211432220
Publication status	Published - Apr 2013

Keywords

Components of variance
incomplete blocks
indirect comparisons
mean-mean multiple comparisons plot

Access to Document

10.1177/0962280211432220

Cite this

@article{505ae4f5ccb941e68d0c5af0332edf20,

title = "Issues in performing a network meta-analysis",

abstract = "The example of the analysis of a collection of trials in diabetes consisting of a sparsely connected network of 10 treatments is used to make some points about approaches to analysis. In particular various graphical and tabular presentations, both of the network and of the results are provided and the connection to the literature of incomplete blocks is made. It is clear from this example that is inappropriate to treat the main effect of trial as random and the implications of this for analysis are discussed. It is also argued that the generalisation from a classic random-effect meta-analysis to one applied to a network usually involves strong assumptions about the variance components involved. Despite this, it is concluded that such an analysis can be a useful way of exploring a set of trials.",

keywords = "Components of variance, incomplete blocks, indirect comparisons, mean-mean multiple comparisons plot",

author = "Stephen Senn and Francois Gavini and David Magrez and Andr{\'e} Scheen",

year = "2013",

month = apr,

doi = "10.1177/0962280211432220",

language = "English",

volume = "22",

pages = "169--189",

journal = "Statistical Methods in Medical Research",

issn = "0962-2802",

publisher = "SAGE Publications Ltd",

number = "2",

}

TY - JOUR

T1 - Issues in performing a network meta-analysis

AU - Senn, Stephen

AU - Gavini, Francois

AU - Magrez, David

AU - Scheen, André

PY - 2013/4

Y1 - 2013/4

N2 - The example of the analysis of a collection of trials in diabetes consisting of a sparsely connected network of 10 treatments is used to make some points about approaches to analysis. In particular various graphical and tabular presentations, both of the network and of the results are provided and the connection to the literature of incomplete blocks is made. It is clear from this example that is inappropriate to treat the main effect of trial as random and the implications of this for analysis are discussed. It is also argued that the generalisation from a classic random-effect meta-analysis to one applied to a network usually involves strong assumptions about the variance components involved. Despite this, it is concluded that such an analysis can be a useful way of exploring a set of trials.

AB - The example of the analysis of a collection of trials in diabetes consisting of a sparsely connected network of 10 treatments is used to make some points about approaches to analysis. In particular various graphical and tabular presentations, both of the network and of the results are provided and the connection to the literature of incomplete blocks is made. It is clear from this example that is inappropriate to treat the main effect of trial as random and the implications of this for analysis are discussed. It is also argued that the generalisation from a classic random-effect meta-analysis to one applied to a network usually involves strong assumptions about the variance components involved. Despite this, it is concluded that such an analysis can be a useful way of exploring a set of trials.

KW - Components of variance

KW - incomplete blocks

KW - indirect comparisons

KW - mean-mean multiple comparisons plot

UR - http://www.scopus.com/inward/record.url?scp=84876727170&partnerID=8YFLogxK

U2 - 10.1177/0962280211432220

DO - 10.1177/0962280211432220

M3 - Article

C2 - 22218368

AN - SCOPUS:84876727170

SN - 0962-2802

VL - 22

SP - 169

EP - 189

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

IS - 2

ER -

Issues in performing a network meta-analysis

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this