Utilizing radar graphs in the visualization of simulation and estimation results in network meta-analysis

The use of network meta-analysis in updating WHO living maternal and perinatal health recommendations

Drawing on two recent examples of WHO living guidelines in maternal and perinatal health, this paper elucidates a pragmatic, stepwise approach to using network meta-analysis (NMA) in guideline development in the presence of multiple treatment options. NMA has important advantages. These include the ability to compare multiple interventions in a single coherent analysis, provide direct estimates of the relative effects of all available interventions, infer indirect effect estimates for interventions not directly compared and generate rankings of the available treatment options. It can be difficult to harness these advantages in the face of a lack of current guidance on using NMA evidence in guideline development, with several challenges emerging. Challenges include the choice of conceptual approach, the volume and complexity of the evidence, the contribution of treatment rankings, and the fact that the preferable treatment is not always obvious. This paper describes a layered approach to resolving these challenges, which supports systematic guideline decision-making and development of trustworthy clinical guidelines when multiple treatment options are available.

Origami plot: a novel multivariate data visualization tool that improves radar chart

OBJECTIVES

We propose the origami plot, which maintains the original functionality of a radar chart and avoids potential misuse of its connected regions, with newly added features to better assist multicriteria decision-making.

STUDY DESIGN AND SETTING

Built upon a radar chart, the origami plot adds additional auxiliary axes and points such that the area of the connected region of all dots is invariant to the ordering of axes. As such, it enables ranking different individuals by the overall performance for multicriteria decision-making while maintaining the intuitive visual appeal of the radar chart. We develop extensions of the origami plot, including the weighted origami plot, which allows reweighting of each attribute to define the overall performance, and the pairwise origami plot, which highlights comparisons between two individuals.

RESULTS

We illustrate the different versions of origami plots using the hospital compare database developed by the Centers for Medicare & Medicaid Services (CMS). The plot shows individual hospital's performance on mortality, readmission, complication, and infection, as well as patient experience and timely and effective care, as well as their overall performance across these metrics. The weighted origami plot allows weighing the attributes differently when some are more important than others. We illustrate the potential use of the pairwise origami plot in electronic health records (EHR) system to monitor five clinical measures (body mass index [BMI]), fasting glucose level, blood pressure, triglycerides, and low-density lipoprotein ([LDL] cholesterol) of a patient across multiple hospital visits.

CONCLUSION

The origami plot is a useful visualization tool to assist multicriteria decision making. It improves radar charts by avoiding potential misuse of the connected regions. It has several new features and allows flexible customization.

Vitruvian plot: a visualisation tool for multiple outcomes in network meta-analysis

OBJECTIVE

A network meta-analysis (NMA) usually assesses multiple outcomes across several treatment comparisons. The Vitruvian plot aims to facilitate communication of multiple outcomes from NMAs to patients and clinicians.

METHODS

We developed this tool following the recommendations on the communication of benefit-risk information from the available literature. We collected and implemented feedback from researchers, statisticians, methodologists, clinicians and people with lived experience of physical and mental health issues.

RESULTS

We present the Vitruvian plot, which graphically presents absolute estimates and relative performance of competing interventions against a common comparator for several outcomes of interest. We use two alternative colour schemes to highlight either the strength of statistical evidence or the confidence in the evidence. Confidence in the evidence is evaluated across six domains (within-study bias, reporting bias, indirectness, imprecision, heterogeneity and incoherence) using the Confidence in Network Meta-Analysis (CINeMA) system.

CONCLUSIONS

The Vitruvian plot allows reporting of multiple outcomes from NMAs, with colourings appropriate to inform credibility of the presented evidence.

Simplified figure to present direct and indirect comparisons: Revisiting the graph 10 years later

A “simplified” figure was proposed in 2011 to summarize the results of controlled trials that evaluate different treatments aimed at the same disease condition. The original criteria for classifying individual binary comparisons included superiority, inferiority and no significance difference; hence, they did not differentiate between no proof of difference vs proof of no difference. We updated the criteria employed in the original “simplified” figure in order to include this differentiation. A revised version of the simplified figure is proposed and described herein. An example of application is also presented. The example is focused on first-line treatments for paroxysmal atrial fibrillation. Three treatments (medical therapy, cryoballoon ablation, radiofrequency ablation) are compared with one another through direct and indirect comparisons.