IL-6 inhibition in the treatment of COVID-19: A meta-analysis and meta-regression

Abstract

Objectives : Multiple RCTs of interkeukin-6 (IL-6) inhibitors in COVID-19 have been published, with conflicting conclusions. We performed a meta-analysis to assess the impact of IL-6 inhibition on mortality from COVID-19, utilising meta-regression to explore differences in study results. Methods : Systematic database searches were performed to identify RCTs comparing IL-6 inhibitors (tocilizumab and sarilumab) to placebo or standard of care in adults with COVID-19. Meta-analysis was used to estimate the relative risk of mortality at 28 days between arms, expressed as a risk ratio. Within-study mortality rates were compared, and meta-regression was used to investigate treatment effect modification. Results : Data from nine RCTs were included. The combined mortality rate across studies was 19% (95% CI: 18, 20%), ranging from 2% to 31%. The overall risk ratio for 28-day mortality was 0.90 (95% CI: 0.81, 0.99), in favour of benefit for IL-6 inhibition over placebo or standard of care, with low treatment effect heterogeneity: I 2 0% (95% CI: 0, 53%). Meta-regression showed no evidence of treatment effect modification by patient characteristics. Trial-specific mortality rates were explained by known patient-level predictors of COVID-19 outcome (male sex, CRP, hypertension), and country-level COVID-19 incidence. Conclusions : IL-6 inhibition is associated with clinically meaningful improvements in outcomes for patients admitted with COVID-19. Long-term benefits of IL-6 inhibition, its effectiveness across healthcare systems, and implications for differing standards of care are currently unknown.

Efficacy and Safety of Immunomodulators in Patients with COVID-19: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials

“…We observed little benefit of IL antagonists, contradicting the results of prior meta-analyses [ 15 , 20 ] because we included a large-scale phase 3 RCT of SAR that reported a negative result [ 26 ]. IL antagonists significantly decreased the mortality rate and the incidence of IMV, primarily based on the effect of TOC, as reported previously [ 15 , 16 , 18 ].…”

Systematic Review and Subgroup Meta-analysis of Randomized Trials to Determine Tocilizumab’s Place in COVID-19 Pneumonia

“…The heterogenous population in RCTs seems to explain that [14,15]. A recent meta-analysis of these RCTs [16] has shown that the overall mortality varies widely across these RCTs (from 2% to 30%); this considerable variation is mainly explained by patient severity at baseline. Tocilizumab seems to be effective in severe patients and subgroup analysis is needed [14][15][16][17].…”

“…A recent meta-analysis of these RCTs [16] has shown that the overall mortality varies widely across these RCTs (from 2% to 30%); this considerable variation is mainly explained by patient severity at baseline. Tocilizumab seems to be effective in severe patients and subgroup analysis is needed [14][15][16][17]. For example the only subgroup analysis on severe patients in RCT was performed by Soin et al in COVINTOC [11] and it supports this assumption: among patients who had severe coronavirus disease 2019 (COVID-19) at baseline, 16% patients died in the tocilizumab group versus 34% in the standard care group (p = 0.04); in COVINTOC severe COVID-19 was defined as respiratory rate of at least 30/min or SpO 2 less than 90% or acute respiratory distress syndrome or septic shock.…”

The Use of Tocilizumab in Patients with COVID-19: A Systematic Review, Meta-Analysis and Trial Sequential Analysis of Randomized Controlled Studies

“…In particular, owing to the publication of concurrent similar research syntheses [55,56], we did not explore secondary outcomes such as progression to mechanical ventilation, time to discharge, LOS, and safety profiles, which had already been addressed by previous works. Eventually, we did not perform meta-regression: in a preceding meta-analysis, there was no evidence of treatment effect modification by patient characteristics [57]. Nonetheless, conventional meta-analyses may be biased due to the ecological fallacy (also known as aggregation bias) since average patient characteristics are regressed against average trial outcomes; instead, individual patient characteristics should be regressed against the individual outcomes in the context of an individual patient data meta-analysis [58].…”