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

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.