The number needed to treat in pairwise and network meta-analysis and its graphical representation

Areti Angeliki Veroniki*, Ralf Bender, Paul Glasziou, Sharon E. Straus, Andrea C. Tricco

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)
32 Downloads (Pure)

Abstract

Objective: The objective of this study was to present ways to graphically represent a number needed to treat (NNT) in (network) meta-analysis (NMA). Study Design and Setting: A barrier to using NNT in NMA when an odds ratio (OR) or risk ratio (RR) is used is the determination of a single control event rate (CER). We discuss approaches to calculate a CER, and illustrate six graphical methods for NNT from NMA. We illustrate the graphical approaches using an NMA of cognitive enhancers for Alzheimer's dementia. Results: The NNT calculation using a relative effect measure, such as OR and RR, requires a CER value, but different CERs, including mean CER across studies, pooled CER in meta-analysis, and expert opinion-based CER may result in different NNTs. An NNT from NMA can be presented in a bar plot, Cates plot, or forest plot for a single outcome, and a bubble plot, scatterplot, or rank-heat plot for ≥2 outcomes. Each plot is associated with different properties and can serve different needs. Conclusion: Caution is needed in NNT interpretation, as considerations such as selection of effect size and CER, and CER assumption across multiple comparisons, may impact NNT and decision-making. The proposed graphs are helpful to interpret NNTs calculated from (network) meta-analyses.

Original languageEnglish
Pages (from-to)11-22
Number of pages12
JournalJournal of Clinical Epidemiology
Volume111
Early online date21 Mar 2019
DOIs
Publication statusPublished - 1 Jul 2019

Fingerprint Dive into the research topics of 'The number needed to treat in pairwise and network meta-analysis and its graphical representation'. Together they form a unique fingerprint.

  • Cite this