Statistical analysis
Sample size calculations were based on the assumed rate of patients in the group of individuals unexposed to DMARDs (0.15). With 5% significance level and 80% power, 1,701 subjects in the exposed group and 850 in the unexposed group were needed to detect a minimum relative risk (RR) of 1.3.
To evaluate the associations between different treatments and the presence of hsCOVID-19 symptoms, Poisson regression models with robust variance estimation were used to estimate RR and 95% confidence intervals (95%CI) (Dong E and Du H, 2020). Models were adjusted by sex, age, diabetes, pulmonary disease, cardiovascular disease, chronic kidney disease, and active cancer or treatment. Model 1 aimed to estimate the association between treatments grouped by drug type (1) bDMARDs; (2) sDMARDs, (3) glucocorticoids, (4) chronic nonsteroidal anti-inflammatory drugs (NSAIDs) and (5) Anti-hypertensive drugs. Then, associations between hsCOVID-19 symptoms were estimated by each individual treatment (with >100 exposed patients; reference category = “unexposed”; Model 2). Finally, as anti-TNFα treatments were the major group of bDMARDs, the effect of each anti-TNFα drug was estimated separately in model 3. Model 3 also included the effect of anti-IL17 and anti-IL23(-12), but anti-IL6 could not be analyzed as a separate group as there were not hsCOVID-19 symptoms reported among individuals exposed to IL-6 antagonists. Interactions between different drug types were also tested (model 4). Models 1 and 2 were furthermore replicated in the subgroup of individuals aged ≤ 60 years (model 5 and 6) and >60 years (model 7 and 8). All analyses were stratified by sex. Finally, the main treatment indications, together with the studied comorbidities (sex, age, cardiovascular disease, diabetes, pulmonary disease, kidney disease and cancer) were used to create a matched dataset for the exposure to each treatment Propensity score matching was applied for the exposure to anti-TNFα, anti-proinflammatory ILs, glucocorticoids (≤10 mg/day in women) and chloroquine/hydroxychloroquine. Statistical analyses were performed using R (R Foundation for Statistical Computing, Vienna, Austria) version 3.5.2.