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letter
. 2020 Sep 5;2(11):e662. doi: 10.1016/S2665-9913(20)30307-6

Mavrilimumab for severe COVID-19

Mohamad Amin Pourhoseingholi a, Sajad Shojaee b, Sara Ashtari b
PMCID: PMC7834396  PMID: 33521662

In The Lancet Rheumatology, Giacomo De Luca and colleagues1 examined whether mavrilimumab added to standard care could improve the clinical outcomes in patients with COVID-19 pneumonia and systemic hyperinflammation in a single-centre prospective cohort study. They compared 13 patients treated with mavrilimumab to 26 patients who received standard care. The analysis showed earlier clinical improvement in the intervention group than in the control group. However, the power of study was low due to the small sample size, and no statistical difference in mortality was found between the two groups (no patients died in the mavrilimumab group vs seven [27%] patients in the control group; p=0·086). The challenges of doing clinical studies to find safe and effective therapies during the COVID-19 pandemic are understandable, with shortfalls of adequate actions against the unknown disease and its complication in resource-limited conditions and given concerns over a potentially high case–fatality rates. However, as Cheung and colleagues caution,2 underpowered studies that are susceptible to type II error could discourage clinicians from using potentially effective treatments against COVID-19 and lead to premature rejection of promising drugs.

Although a prospective cohort, De Luca and colleagues' study1 was done at a single centre, and patients were matched with a control group. As they mentioned in their limitations section, the absence of a pre-established randomisation process can introduce risks for selection bias. Although the distribution of demographic variables for both groups indicated no significant differences, one should note that this lack of difference might be due to low sample size, because a small sample size is more likely to show no difference according to type II error. In this case, the authors could use multivariate analysis (including a Cox regression model) to control for the potential confounders (eg, the predominance of male participants and longer fever duration in the intervention group than in the control group).

In summary, no strong conclusions about the effects of mavrilimumab in COVID-19 can be made until an appropriately powered trial has been done with appropriate statistical analysis to avoid potential bias.

Acknowledgments

We declare no competing interests.

References

  • 1.De Luca G, Cavalli G, Campochiaro C. GM-CSF blockade with mavrilimumab in severe COVID-19 pneumonia and systemic hyperinflammation: a single-centre, prospective cohort study. Lancet Rheumatol. 2020;2:e465–e473. doi: 10.1016/S2665-9913(20)30170-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Cheung MP, Lee TC, Tan DHS. Generating randomized trial evidence to optimize treatment in the COVID-19 pandemic. CMAJ. 2020;192:405–407. doi: 10.1503/cmaj.200438. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from The Lancet. Rheumatology are provided here courtesy of Elsevier

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