Literature DB >> 34322372

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

Valeria Fadda1, Laura Bartoli1, Elisa Ferracane1, Sabrina Trippoli1, Andrea Messori2.   

Abstract

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. ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.

Entities:  

Keywords:  Direct comparisons; Indirect comparison; Meta-analysis; Outcome research; Randomised controlled trials; Statistics

Year:  2021        PMID: 34322372      PMCID: PMC8299911          DOI: 10.5662/wjm.v11.i4.228

Source DB:  PubMed          Journal:  World J Methodol        ISSN: 2222-0682


Core Tip: A “simplified” figure was proposed in 2011 to summarize the results of controlled trials that evaluate different treatments aimed at the same disease condition. This graphical tool presents the network geometry along with the results of the analysis. The original criteria for classifying individual binary comparisons (direct or indirect comparisons) did not differentiate between no proof of difference vs proof of no difference. We have therefore updated the criteria employed in the original “simplified” figure to include this differentiation.

TO THE EDITOR

In 2011, Fadda and coworkers published in the BMJ the proposal of a simplified graph that, in the context of a network meta-analysis, presents the results of direct and indirect comparisons[1]. In 2019, another graph with very similar characteristics was proposed by De Vecchis et al[2]. Both of these graphs adopt the symbol “+” for superiority, “-“ for inferiority, and “=” for the remaining cases. Differentiating between no proof of difference (with P > 0.05) and proof of no difference (with P > 0.05 and Pequivalence < 0.05) is increasingly recognised to be important[3]; the same applies to differentiation between no proof of difference and proof of non-inferiority (with P > 0.05 and Pnon-inferiority < 0.05, respectively). Since the two graphs of Fadda et al[1] and De Vecchis et al[2] do not include this differentiation, we propose to limit the symbol “=” to cases of equivalence and to adopt the symbol “NI” for non-inferiority or “ND” for the remaining cases. The suffix “t” remains useful because it identifies cases where the binary comparison shows a trend in favour of a treatment though in the absence of a statistically significant difference. An example of the revisited graph is presented in Figure 1 that compares three first line treatments in paroxysmal atrial fibrillation[4-8].
Figure 1

Direct and indirect comparisons across three first-line treatments for patients with paroxysmal atrial fibrillation. The comparisons of radiofrequency vs medical therapy and cryoballoon vs medical therapy are based on three[4-6] and two trials[7,8], respectively.

Direct and indirect comparisons across three first-line treatments for patients with paroxysmal atrial fibrillation. The comparisons of radiofrequency vs medical therapy and cryoballoon vs medical therapy are based on three[4-6] and two trials[7,8], respectively. In the field of network meta-analysis, the issue of graphical communication is complex, and the debate is still ongoing[9-15]. While the objective of describing the network geometry is quite straightforward[9,10], communication becomes more complex when it comes to presenting the results of the analysis[11-15]. The graphical proposal described herein is aimed at presenting the network geometry along with the results of the analysis. In our view, despite some unavoidable aspects of complexity, this tool deserves to be used particularly when the number of comparators is small.
  14 in total

1.  Network meta-analysis. Results can be summarised in a simple figure.

Authors:  Valeria Fadda; Dario Maratea; Sabrina Trippoli; Andrea Messori
Journal:  BMJ       Date:  2011-03-23

2.  Graphical representation of network meta-analysis: an iconographic support to the complexity of multiple data comparisons.

Authors:  Renato De Vecchis; Carmelina Ariano; Angelos Rigopoulos; Michel Noutsias
Journal:  Eur J Clin Pharmacol       Date:  2018-09-10       Impact factor: 2.953

3.  Differentiating between "no proof of difference" and "proof of no difference" for new oral anticoagulants.

Authors:  Andrea Messori; Valeria Fadda; Roberta Gatto; Dario Maratea; Sabrina Trippoli
Journal:  BMJ       Date:  2014-03-06

4.  Is providing uncertainty intervals in treatment ranking helpful in a network meta-analysis?

Authors:  Areti Angeliki Veroniki; Sharon E Straus; Gerta Rücker; Andrea C Tricco
Journal:  J Clin Epidemiol       Date:  2018-02-10       Impact factor: 6.437

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

Authors:  Svenja E Seide; Katrin Jensen; Meinhard Kieser
Journal:  Res Synth Methods       Date:  2020-05-04       Impact factor: 5.273

6.  Radiofrequency ablation as initial therapy in paroxysmal atrial fibrillation.

Authors:  Jens Cosedis Nielsen; Arne Johannessen; Pekka Raatikainen; Gerhard Hindricks; Håkan Walfridsson; Ole Kongstad; Steen Pehrson; Anders Englund; Juha Hartikainen; Leif Spange Mortensen; Peter Steen Hansen
Journal:  N Engl J Med       Date:  2012-10-25       Impact factor: 91.245

7.  Radiofrequency ablation vs antiarrhythmic drugs as first-line treatment of paroxysmal atrial fibrillation (RAAFT-2): a randomized trial.

Authors:  Carlos A Morillo; Atul Verma; Stuart J Connolly; Karl H Kuck; Girish M Nair; Jean Champagne; Laurence D Sterns; Heather Beresh; Jeffrey S Healey; Andrea Natale
Journal:  JAMA       Date:  2014-02-19       Impact factor: 56.272

8.  Cryoballoon Ablation as Initial Therapy for Atrial Fibrillation.

Authors:  Oussama M Wazni; Gopi Dandamudi; Nitesh Sood; Robert Hoyt; Jaret Tyler; Sarfraz Durrani; Mark Niebauer; Kevin Makati; Blair Halperin; Andre Gauri; Gustavo Morales; Mingyuan Shao; Jeffrey Cerkvenik; Rachelle E Kaplon; Steven E Nissen
Journal:  N Engl J Med       Date:  2020-11-16       Impact factor: 91.245

9.  The Kilim plot: A tool for visualizing network meta-analysis results for multiple outcomes.

Authors:  Michael Seo; Toshi A Furukawa; Areti Angeliki Veroniki; Toby Pillinger; Anneka Tomlinson; Georgia Salanti; Andrea Cipriani; Orestis Efthimiou
Journal:  Res Synth Methods       Date:  2020-07-16       Impact factor: 5.273

10.  Graphical tools for network meta-analysis in STATA.

Authors:  Anna Chaimani; Julian P T Higgins; Dimitris Mavridis; Panagiota Spyridonos; Georgia Salanti
Journal:  PLoS One       Date:  2013-10-03       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.