Identification of Clinical Response Predictors of Tocilizumab Treatment in Patients with Severe COVID-19 Based on Single-Center Experience

Abstract

Hyperinflammation in COVID-19 plays a crucial role in pathogenesis and severity; thus, many immunomodulatory agents are applied in its treatment. We aimed to identify good clinical response predictors of tocilizumab (TCZ) treatment in severe COVID-19, among clinical, laboratory, and radiological variables. We conducted a prospective, observational study with 120 patients with severe COVID-19 not improving despite dexamethasone (DEX) treatment. We used parametric and non-parametric statistics, univariate logistic regression, receiver operating characteristic (ROC) curves, and nonlinear factors tertile analysis. In total, 86 (71.7%) patients achieved the primary outcome of a good clinical response to TCZ. We identified forty-nine predictive factors with potential utility in patient selection and treatment monitoring. The strongest included time from symptom onset between 9 and 12 days, less than 70% of estimated radiological lung involvement, and lower activity of lactate dehydrogenase. Additional predictors were associated with respiratory function, vitamin D concentration, comorbidities, and inflammatory/organ damage biomarkers. Adverse events analysis proved the safety of such a regimen. Our study confirmed that using TCZ early in the hyperinflammatory phase, before severe respiratory failure development, is most beneficial. Considering the described predictive factors, employing simple and widely available laboratory, radiological, and clinical tools can optimize patient selection for immunomodulatory treatment with TCZ.