Outputs from living evidence syntheses projects have been used widely during the pandemic by guideline developers to form evidence-based recommendations. However, the needs of different stakeholders cannot be accommodated by solely providing pre-defined non amendable numerical summaries. Stakeholders also need to understand the data and perform their own exploratory analyses. This requires resources, time, statistical expertise, software knowledge as well as relevant clinical expertise to avoid spurious conclusions. To assist them, we created the metaCOVID application which, based on automation processes, facilitates the fast exploration of the data and the conduct of sub-analyses tailored to end-users needs. metaCOVID has been created in R and is freely available as an R-Shiny application. Based on the COVID-NMA platform (https://covid-nma.com/) the application conducts living meta-analyses of randomized controlled trials related to COVID-19 treatments and vaccines for several outcomes. Several options are available for subgroup and sensitivity analyses. The results are presented in downloadable forest plots. We illustrate metaCOVID through three examples involving well-known treatments and vaccines for COVID-19. The application is freely available from https://covid-nma.com/metacovid/.
Keywords: data visualization; dynamic evidence synthesis; medical decision making; online software tool.
© 2023 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.