Two observational studies from Italy and Spain were conducted, approved by the Internal Review Boards (IRBs) of each institution. Entry criteria for each institution included patients with radiologically defined COVID-19 pneumonia and laboratory-confirmed infection, as diagnosed by a positive SARS-CoV-2 RT-PCR (reverse transcription PCR) test by nasopharyngeal swab. All patients enrolled had a blood oxygen saturation (SaO2) < 94% at baseline but did not require mechanical ventilation. The Pisa, Italy cohort included all consecutive cases with SARS-CoV-2 pneumonia and PaO2/FiO2 (P/F) ratio of <300 mmHg at admission diagnosed between the period of 7 and 31 March 2020 and had moderate-to-severe or severe disease. The COVID-AGE study from Albacete, Spain (NCT04362943) was conducted at Complejo Hospitalario Universitario of Albacete, dedicated to older adults; thus, baricitinib doses were lower than in Italy. The Albacete cohort included patients ≥70 years with SARS-CoV-2 pneumonia, diagnosed between 9 March and 20 April 2020, not requiring mechanical ventilation, and again having moderate-to-severe or severe disease.

Written informed consent was obtained from each patient in Italy and verbal informed consent in Spain as approved by the local IRB. Baricitinib was administered at a dose of 4 mg/day for 14 days in conjunction with standard of care in Italy and at lower doses of 2 or 4 mg/day for 3 to 11 days in the Spanish cohort because of age-related factors. Any patient with confirmed COVID-19 infection who received at least three doses of baricitinib was included in the intent-to-treat analysis. Standard clinical and laboratory data were collected including patients’ demographics, comorbidities, oxygen support, adverse events, laboratory values, concomitant therapies, and clinical outcomes. Exclusion criteria in all patients included a history of active or latent tuberculosis infection (QuantiFERON Plus-test positivity, QIAGEN, Germany), pregnancy, and/or lactation. The primary outcome was death from any cause or intensive care unit admission needing invasive mechanical ventilation during hospitalization.

For both cohorts, propensity score matching was used to create the control selection sample using patients admitted in the same period of time in both hospitals, not treated with baricitinib. Cases and controls were matched for relevant predictors of respiratory failure and death, as well as baseline treatments. The following variables, all of them clinically relevant for mortality and respiratory failure, were included in the propensity score estimation: age, sex, chronic obstructive pulmonary disease, arterial hypertension, cardiovascular disease, diabetes mellitus, chronic kidney failure, Charlson comorbidity index, baseline P/F ratio, lymphocyte count, therapy with steroids, LMWH, and “antiviral” therapy with hydroxychloroquine or protease inhibitors (lopinavir/ritonavir). Propensity score matching was conducted with the statistical package MatchIt (v4.0.2), using the recommendations from Ho et al. (50) to improve parametric models and preprocessing of nonparametric data. After the propensity score was determined for each patient, those treated with baricitinib were matched to 1:1 to a control patient using a greedy matching procedure with replacement, targeting the average treatment effect on the treated replacement. Continuous variables were tested using Wilcoxon-Mann-Whitney rank sum test; categorical variables were tested using Pearson’s chi-square or Fisher’s exact test. For every test performed, the P value was always above 0.05, and therefore, we can say that the groups were homogeneous regarding the control variables. Validity of the balance in potential confounding variables was assessed visually with normality plots using the “R” function [“geom:smooth()” using formula “y ~ x”], also using the Wilcoxon rank sum test with continuity correction analyses for continuous variables, and with Pearson’s chi-square tests for categorical ones. Although the matching figures were not perfect, no statistical differences were found for any variables included in the propensity score in the merged Pisa and Albacete cohorts. Mortality reduction was analyzed with Cox proportional hazard models adjusted for all the variables included in the propensity score matching, to further control for the small deviations in the matching procedure, plus the presence of active cancer, alanine aminotransferase, and antibiotic use. Safety data are presented in a descriptive manner. Last, individual and merged data from Pisa and Albacete were used to analyze the primary outcome, survival, or mechanical ventilation, in baricitinib and control groups using Kaplan-Meier analysis, including 95% CIs. The global significance was determined using a Peto-Peto analysis that prioritizes the first part of the curves but with increased robustness compared to Taron-Ware analysis. This decision was taken after the observation that the main differences between baricitinib and control patients were present from the beginning of the treatment. Statistical significance was established at P < 0.05 using a two-sided test statistic. All analyses were done using the statistical package R.

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