Multivariate Cox regression models and Kaplan–Meier survival curves were used to compare survival among treatment groups while controlling for demographics, preexisting medical conditions, and clinical disease severity

Bivariate comparisons of the 4 groups were made using analysis of variance or Kruskal–Wallis tests for continuous variables and chi-square tests or Fisher exact tests for categorical variables

A propensity score was created for each patient based on the set of patient characteristics used in the Cox regression model

1 to 1 matches of patients given hydroxychloroquine (either hydroxychloroquine alone or in combination with azithromycin) and patients not given hydroxychloroquine based on the exact propensity score were observed; the resulting matched group status was placed into its own Cox regression model as a mortality predictor with a Kaplan–Meier plot summarizing the survival curves of the two matched groups