Figure 1 . Meta-analysis of placebo-controlled randomized trials of fluvoxamine (2x100 or 3x100 mg/day over 10 to 15 days) in adult, non-vaccinated symptomatic mild COVID-19 outpatients evaluating the effects on disease progression. Implemented are frequentist and Bayesian random-effects pooling methods used also in the meta-analysis by Lee et al. 3 [restricted maximum likelihood estimator of across study variance in the frequentist analysis, and weakly informative neutral prior for the effect – 0 for ln(RR) and 0.355 for its standard deviation – and half-cauchy with scale 0.10 for the heterogeneity parameter]. The differences vs. the published meta-analyses 3, 4 are in that: (i) it includes data from the Korean trial (Seo et al. 8) and (ii) uses Hartung-Knapp-Sidik-Jonkman correction to calculated frequentist confidence intervals, as recommended 9. A.Meta-analysis of study-defined primary outcomes (explained in the text). Data for Stop COVID 1 5, TOGETHER 7and the Korean trial (Seo et al. 8) are taken from the respective publications. Data for Stop COVID 2 are not publicly available and were taken from the meta-analysis by Lee et al.3. B . Meta-analysis of hospitalizations. Data for TOGETHER trial 7 and the Korean trial8 are taken from the respective publications. Data for Stop COVID 1 and 2 trials are taken from the meta-analysis by Lee et al.3 – the principal investigator of the Stop COVID trials is one of the co-authors, hence data should be considered accurrate.
Bayesian analysis was performed using package bayesmeta10 in R (as in the published meta-analysis3), frequentist analysis was performed using packagemeta (11) in R.