Feasibility study for interactive reporting of network meta-analysis: experiences from the development of the MetaInsight COVID-19 app for stakeholder exploration, re-analysis and sensitivity analysis from living systematic reviews

Abstract

Abstract Background Network meta-analysis (NMA) has been increasingly adopted worldwide by Cochrane reviews, guideline developers and decision-making bodies to identify optimal treatment choices. However, NMA results are often produced statically, not allowing stakeholders to ‘dig deeper’ and interrogate with their own judgement. Additionally, amid the COVID-19 pandemic, unnecessary or duplicated reviews have been proposed which analyse from the same pool of evidence. We developed the ‘MetaInsight COVID-19’ app as a prototype for an interactive platform to eliminate such duplicated efforts, by empowering users to freely analyse the data and improve scientific transparency. Methods MetaInsight COVID-19 (https://crsu.shinyapps.io/metainsightcovid/) was developed to conduct NMA with the evolving evidence on treatments for COVID-19. It was updated weekly between 19th May – 19th Oct 2020, incorporating new evidence identified from a living systematic review. Results The app includes embedded functions to facilitate study selection based on study characteristics, and displays the synthesised results in real time. It allows both frequentist and Bayesian NMA to be conducted as well as consistency and heterogeneity assessments. A demonstration of the app is provided and experiences of building such a platform are discussed. Conclusions MetaInsight COVID-19 allows users to take control of the evidence synthesis using the analytic approach they deem appropriate to ascertain how robust findings are to alternative analysis strategies and study inclusion criteria. It is hoped that this app will help avoid many of the duplicated efforts when reviewing and synthesising the COVID-19 evidence, and, in addition, establish the desirability of an open platform format such as this for interactive data interrogation, visualisation, and reporting for any traditional or ‘living’ NMA.