Tocilizumab administration is associated with the reduction in biomarkers of coronavirus disease 2019 infection.
Timotius Ivan HariyantoAndree KurniawanPublished in: Journal of medical virology (2020)
Coronavirus disease 2019 (COVID-19) has caused a significant impact on all aspects of life, with the number of death cases still increasing. Therefore, identification of potential treatment for reducing the severity of the disease is important. Currently, the data regarding the effectiveness of tocilizumab as treatment agents for COVID-19 infection is still conflicting. This study aims to give clear evidence regarding the potential benefit of tocilizumab in reducing the biomarkers of COVID-19 infection. We systematically searched the PubMed Central database using specific keywords related to our aims until July 24th, 2020. All articles published on COVID-19 and tocilizumab were retrieved. A total of 9 studies with a total of 577 patients were included in our analysis. Our meta-analysis showed that tocilizumab treatment is associated with reduction of C-reactive protein (mean difference [MD]: -106.69 mg/L [95% confidence interval [CI]: -146.90, -66.49 mg/L], p < .00001; I2 = 98%, random-effect modeling), d-dimer (MD: -3.06 mg/L [95% CI: -5.81, -0.31 mg/L], p = .03; I2 = 98%, random-effect modeling), Ferritin (MD: -532.80 ng/ml [95% CI: -810.93, -254.67 ng/ml], p = .0002; I2 = 25%, random-effect modeling), procalcitonin (MD: -0.67 ng/ml [95% CI: -1.13, -0.22 ng/ml], p = .004; I2 = 92%, random-effect modeling], and increment in the levels of lymphocyte count (MD: 0.36 × 103 /μl [95% CI: 0.18, 0.54 × 103 /μl], p < .0001; I2 = 88%, random-effect modeling). Administration of tocilizumab is effective in reducing the biomarkers of the COVID-19 infection.
Keyphrases
- coronavirus disease
- rheumatoid arthritis
- juvenile idiopathic arthritis
- systematic review
- randomized controlled trial
- molecular dynamics
- rheumatoid arthritis patients
- sars cov
- emergency department
- risk assessment
- respiratory syndrome coronavirus
- newly diagnosed
- ejection fraction
- prognostic factors
- machine learning
- meta analyses
- human health