Identification of Predictive Markers of Response to Immunomodulators in the Treatment of COVID-19 Patients.

Abstract

Proper identification of patients at risk of developing serious disease in the context of SARS-CoV-2 infection, as well as the initiation of early treatment, is one of the fundamental elements for successful management of COVID-19. The main objective of this study was to evaluate the usefulness of serum biomarkers (neutrophils, lymphocytes, C-reactive protein, lactate dehydrogenase, D-dimer, ferritin, and interleukin-6) to predict the early response to immunosuppressant therapy in COVID-19 patients. This is a case-control study nested in a retrospective cohort, which included hospitalized patients with interstitial pneumonia and with elevation of some proinflammatory parameters. Each of the individuals who died during the 28-day follow-up was defined as a case. For each case, 4 controls were selected, matched by age, gender, and comorbidities. The initial cohort included 856 patients. The incidence of therapeutic failure in the cohort was 14%, thus we identified a total of 120 cases. After the application of a Cox regression model, high serum concentrations of LDH (> 451 IU/L), ferritin (> 1,014 ng/mL) and D-Dimer (> 1,300 ng/mL) were identified as predictors of poor response to treatment. Highly-specific cut-off points could not be established for any of these biomarkers. Some inflammatory biomarkers, such as LDH, ferritin, and D-dimer, may be helpful in identifying patients for whom an early immunomodulatory therapeutic intervention should be considered in the treatment of COVID-19 patients with pneumonia.