Abstract
BackgroundNetwork 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.MethodsMetaInsight 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.ResultsThe 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.ConclusionsMetaInsight 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.
Highlights
Network meta-analysis (NMA) has been increasingly adopted worldwide by Cochrane reviews, guideline developers and decision-making bodies to identify optimal treatment choices
MetaInsight Traditionally NMA is conducted with statistical software such as WinBUGS, OpenBUGS, STATA or R, which can form a barrier for people who are inexperienced with such software but have knowledge of NMA
Retrieval of data The COVID-NMA initiative website was monitored during 19th May – 19th October 2020; any new evidence was added to our app weekly through a semi-automated process
Summary
Network meta-analysis (NMA) has been increasingly adopted worldwide by Cochrane reviews, guideline developers and decision-making bodies to identify optimal treatment choices. Traditional meta-analysis, or ‘pairwise meta-analysis’, is used to compare two interventions or treatment options It is limited in its ability to answer clinically relevant questions, such as the ‘most’ effective intervention where three or more are involved. NMA has been increasingly adopted worldwide in recent years by Cochrane reviews, guideline developers and decisionmaking bodies to identify the optimal treatment choices for a given indication. An increasing number of protocols from researchers and clinicians worldwide have been registered, aiming to synthesise evidence from randomised trials and/or observational studies of one or more interventions, investigating outcomes such as efficacy and safety for COVID-19 patients of graded severity. As of 19th October 2020, 338 systematic review (SR) protocols of treatment for COVID-19 have been registered in the international SR registry, PROSPERO [9]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
