Outcome measures, stopping rules, and statistical analysis
APPENDIX
The primary measure was the rate of viral clearance, expressed as a slope coefficient and presented as a half-life. This was estimated under a Bayesian hierarchical linear model fitted to the daily logUnder the linear model, for each intervention, the treatment effect β is encoded as a multiplicative term on the time since randomization: eAll analyses were done in a modified intention-to-treat (mITT) population, comprising patients who had >3 days follow-up qPCR data. The safety population includes all patients who received at least one dose of the intervention. A series of linear and nonlinear Bayesian hierarchical models were fitted to the serial viral quantitative PCR (qPCR) data (Appendix 4). For the pharmacokinetic analysis, a previously developed two-compartment disposition model with four transit compartments adjusted for body weight was fitted to the plasma ivermectin levels (This report describes the ivermectin results compared with no treatment, and also includes the unblinded results for the first 10 patients who received casirivimab/imdevimab (recruited until December 16, 2021) to illustrate the pharmacometric method’s sensitivity. All data analysis was done in R version 4.0.2. Model fitting was done in 