Approaches to interpreting and choosing the best treatments in network meta-analyses

L Mbuagbaw; B Rochwerg; R Jaeschke; D Heels-Andsell; W Alhazzani; L Thabane; Gordon H Guyatt

doi:10.1186/s13643-017-0473-z

Approaches to interpreting and choosing the best treatments in network meta-analyses

Syst Rev. 2017 Apr 12;6(1):79. doi: 10.1186/s13643-017-0473-z.

Authors

L Mbuagbaw^{1

2

3}, B Rochwerg^{1

4}, R Jaeschke^{1

4}, D Heels-Andsell¹, W Alhazzani^{1

4}, L Thabane^{1

2

5

6

7

8}, Gordon H Guyatt^{9

10

11}

Affiliations

¹ Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
² Biostatistics Unit, Father Sean O'Sullivan Research Centre, St Joseph's Healthcare, Hamilton, ON, Canada.
³ Centre for Development of Best Practices in Health (CDBPH), Yaoundé Central Hospital, Yaoundé, Cameroon.
⁴ Department of Medicine, McMaster University, Hamilton, ON, Canada.
⁵ Department of Paediatrics, McMaster University, Hamilton, ON, Canada.
⁶ Centre for Evaluation of Medicine, St Joseph's Healthcare-Hamilton, Hamilton, ON, Canada.
⁷ Population Health Research Institute, Hamilton Health Sciences, Hamilton, ON, Canada.
⁸ Department of Anaesthesia, McMaster University, Hamilton, ON, Canada.
⁹ Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada. guyatt@mcmaster.ca.
¹⁰ Department of Medicine, McMaster University, Hamilton, ON, Canada. guyatt@mcmaster.ca.
¹¹ CLARITY Research Group, Department of Clinical Epidemiology & Biostatistics, McMaster University, Room 2C12, 1200 Main Street West, Hamilton, ON, L8N 3Z5, Canada. guyatt@mcmaster.ca.

Abstract

When randomized trials have addressed multiple interventions for the same health problem, network meta-analyses (NMAs) permit researchers to statistically pool data from individual studies including evidence from both direct and indirect comparisons. Grasping the significance of the results of NMAs may be very challenging. Authors may present the findings from such analyses in several numerical and graphical ways. In this paper, we discuss ranking strategies and visual depictions of rank, including the surface under the cumulative ranking (SUCRA) curve method. We present ranking approaches' merits and limitations and provide an example of how to apply the results of a NMA to clinical practice.

Keywords: Advantages; Limitations; Network meta-analysis; Ranking; SUCRA.

Publication types

Editorial

MeSH terms

Data Interpretation, Statistical*
Humans
Meta-Analysis as Topic*
Randomized Controlled Trials as Topic
Sepsis / therapy
Treatment Outcome