The number needed to treat in pairwise and network meta-analysis and its graphical representation
Veroniki AA, Bender R, Glasziou P, Straus SE, Tricco AC. The number needed to treat in pairwise and network meta-analysis and its graphical representation. Journal of Clinical Epidemiology. 2019;111:11-22. DOI: 10.1016/j.jclinepi.2019.03.007.
- The number needed to treat (NNT) is an absolute measure of effect used to communicate the effectiveness or safety of an intervention, and is relatively easy to understand
- It specifies the average number of patients who need to be treated to achieve treatment success in one patient compared to placebo or another treatment
- The NNT calculation using a relative effect measure, such as odds ratio and risk ratio, requires a control event rate (CER). However, different CERs, such as mean CER across studies, pooled CER in a meta-analysis, expert opinion-based CER, and a range of possible CER values may impact the magnitude and direction of the NNT
- The graphical representation of NNTs from NMA is crucial to ease interpretation of results. We present six graphical approaches for NNT from NMA and discuss their properties
- A NNT may 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
- The Cates plot, bubble plot, and rank-heat plot do not depict the NNT uncertainty, which can impact interpretation. If uncertainty around NNT should be considered in decision-making, then a bar plot or a forest plot can be used
- The Cates plot is suggested if the corresponding effect estimate is statistically significant and the confidence interval is not too wide
- 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 graphs we propose are helpful to interpret NNTs calculated from (network) meta-analyses
Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review
Zarin W, Veroniki AA, Nincic V, Vafaei A, Reynen E, Motiwala SS, Antony J, Sullivan SM, Rios P, Daly C, Ewusie J, Petropoulou M, Nikolakopoulou A, Chaimani A, Salanti G, Straus SE, Tricco AC. Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review. BMC Med. 2017;15(1):3. DOI: 10.1186/s12916-016-0764-6.
- This scoping review revealed several reporting deficiencies and shortcuts in knowledge synthesis methods
- Education amongst the research community is required to improve the quality of reporting and methodological quality of published network meta-analyses (NMAs)
- The need for improving the methodological and reporting characteristics of network meta-analyses (NMAs) was identified, which is useful to facilitate decision making
- The database of network meta-analysis (NMA) characteristics generated from this review is being used for future research to advance the science of knowledge synthesis, including a recent publication comparing five knowledge synthesis approaches commonly used to assess clinical interventions
Bibliographic study showed improving statistical methodology of network meta-analyses published between 1999 and 2015
Petropoulou M, Nikolakopoulou A, Veroniki AA, Rios P, Vafaei A, Zarin W, Giannatsi M, Sullivan S, Tricco AC, Chaimani A, Egger M, Salanti G. Bibliographic study showed improving statistical methodology of network meta-analyses published between 1999 and 2015. J Clin Epidemiol. 2017;82:20-8. DOI: 10.1016/j.jclinepi.2016.11.002.
- The study showed that the undertaking and reporting of statistical methods for network meta-analysis have significantly improved over the past 16 years
- The descriptions of the structural characteristics of network meta-analyses can be used to develop simulation studies and further develop methods in the field
A scoping review of indirect comparison methods and applications using individual patient data
Veroniki AA, Straus SE, Soobiah C, Elliott MJ, Tricco AC. A scoping review of indirect comparison methods and applications using individual patient data. BMC Med Res Methodol. 2016;16:47. DOI: 10.1186/s12874-016-0146-y.
- Highlighted the need for improving the methodological and reporting characteristics of individual patient data network meta-analyses, which is essential to ensure accuracy in clinical decisions
- One in three indirect comparison methods modeling individual patient data adjusted results from different trials to estimate effects as if they had come from the same, randomized, population
- Key methodological and reporting elements (e.g., evaluation of consistency, existence of study protocol) were often missing from an indirect comparison papers
- The methods identified in this study can be used in future individual patient data network meta-analyses
Category : KS Projects
Date : 30 Oct 2017