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J Clin Epidemiol. 2019 Jul;111:11-22. doi: 10.1016/j.jclinepi.2019.03.007. Epub 2019 Mar 21.

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

Author information

1
Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, East Building, Toronto, Ontario, M5B 1T8, Canada; Department of Primary Education, School of Education,University of Ioannina, Ioannina, Greece; Institute of Reproductive and Developmental Biology, Department of Surgery & Cancer, Faculty of Medicine, Imperial College, London W12 0NN, UK. Electronic address: averonik@cc.uoi.gr.
2
Department of Medical Biometry, Institute for Quality and Efficiency in Health Care (IQWiG), Im Mediapark 8, 50670 Cologne, Germany.
3
Centre for Research on Evidence Based Practice, Bond University, Gold Coast, Australia.
4
Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, East Building, Toronto, Ontario, M5B 1T8, Canada; Department of Geriatric Medicine, University of Toronto, Toronto, Ontario, Canada.
5
Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, East Building, Toronto, Ontario, M5B 1T8, Canada; Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th floor, Toronto, Ontario, M5T 3M7, Canada.

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.

KEYWORDS:

Graphical displays; Multiple outcomes; Multiple treatment meta-analysis; Number needed to harm; Presentation results; Rank-heat plot

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