Efficiency of il-6 inhibitor (olokizumab) in suppressing inflammation in patients with moderate COVID-19 pneumonia

Aim. To study the efficiency of IL-6 inhibitor olokizumab in suppressing the inflammation and improving treatment outcomes in patients with moderate COVID-19 pneumonia.

Materials and Methods. We enrolled 48 patients with confirmed COVID-19 pneumonia who had indications for the treatment with olokizumab. Treatment group (n = 29) included patients who received a single subcutaneous injection of olokizumab (0.4 mL, 160 mg/mL) while placebo group (n = 19) included those who did not receive the drug because of contraindications. Inflammatory markers (C-reactive protein, white blood cell count, lymphocyte count, ferritin and D-dimer) have been evaluated on the 1st and the 5th day after the administration of olokizumab. Efficiency of olokizumab was assessed by the treatment outcome and suppression of cytokine storm.

Results. At the 5th day, SpO2 was 90% (88; 92-93) in both groups, yet none of the patients in the treatment group required a mechanical ventilation, in contrast to 21.1% patients in the placebo group (p = 0.001). Inflammatory parameters were also reduced in the treatment group according to the measurements of serum C-reactive protein (5.6 (1.8;13.5) and 23 (17;92.5) mg/L in the treatment and placebo group, respectively, p = 0.0002) and white blood cell count (5.9 (4.8;6.2) and 7.6 (6.6;12 )*109 /L in the treatment and placebo group, respectively, p=0.03). No statistically significant differences were registered regarding serum ferritin (325 (200; 700) and 215 (186; 526) ng/mL, p = 0.41), D-dimer (827 (378; 1940) and 1464 (677; 4600) ng FEU/mL, p = 0.16) and lymphocyte count (1.3 (0.8; 2.1) and 1.5 (1; 2.1)*109 /L, p =0.44). Death was registered in 3.5% and 21.1% of patients in the treatment and placebo group, respectively, (p = 0.05).

Conclusion. Olokizumab ameliorated the progression of COVID-19 pneumonia, improved treatment outcomes and reduced systemic inflammation.

1. WHO. WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020. Available at: https:// www.who.int/dg/speeches/detail/who-director-general-sopening-remarks-at-the-media-briefing-on-covid-19---11- march-2020. Accessed: 29.07.2020.

2. WHO. Coronavirus disease (COVID-19). Situation Report – 182. Available at: https://www.who.int/docs/ default-source/coronaviruse/situation-reports/20200720- covid-19-sitrep-182.pdf?sfvrsn=60aabc5c_2. Accessed: 29.07.2020.

3. Wallinga J, Lipsitch M. How generation intervals shape the relationship between growth rates and reproductive numbers. Proc Biol Sci. 2007;274(1609):599-604. https://doi. org/10.1098/rspb.2006.3754

4. Nishiura H, Linton NM, Akhmetzhanov AR. Serial interval of novel coronavirus (COVID-19) infections. Int J Infect Dis. 2020;93:284-286. https://doi.org/10.1016/j.ijid.2020.02.060

5. Park M, Cook AR, Lim JT, Sun Y, Dickens BL. A Systematic Review of COVID-19 Epidemiology Based on Current Evidence. J. Clin. Med. 2020;9(4):967. https://doi.org/10.3390/jcm9040967

6. Miller JC. A note on the derivation of epidemic final sizes. Bull Math Biol. 2012;74(9):2125-2141. https://doi.org/10.1007/ s11538-012-9749-6

7. Rodpothong P, Auewarakul P. Viral evolution and transmission effectiveness. World J Virol. 2012;1(5):131-134. https://doi. org/10.5501/wjv.v1.i5.131

8. Cori A, Ferguson NM, Fraser C, Cauchemez S. A new framework and software to estimate time-varying reproduction numbers during epidemics. Am J Epidemiol. 2013;178(9):1505- 1512. https://doi.org/10.1093/aje/kwt133

9. Stolwijk AM, Straatman H, Zielhuis GA. Studying seasonality by using sine and cosine functions in regression analysis. J Epidemiol Community Health. 1999;53(4):235-238. https:// doi.org/10.1136/jech.53.4.235

10. WHO. Coronavirus disease (COVID-19). Situation Report – 46. Available at: https://www.who.int/docs/default-source/ coronaviruse/situation-reports/20200327-sitrep-67-covid-19. pdf?sfvrsn=b65f68eb_4. Accessed: 29.07.20.