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Review 1: "IL-6 and IL-10 as predictors of disease severity in COVID 19 patients: Results from Meta-analysis and Regression"

This pre-print says that higher levels of cytokines IL-6 and IL-10 are associated with increased severity of COVID-19. Reviewer consensus suggests this well-conducted study provides scientific evidence of potential prognostic markers that could be useful in clinical care.

Published onSep 30, 2020
Review 1: "IL-6 and IL-10 as predictors of disease severity in COVID 19 patients: Results from Meta-analysis and Regression"
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key-enterThis Pub is a Review of
IL-6 and IL-10 as predictors of disease severity in COVID 19 patients: Results from Meta-analysis and Regression

Aims: SARS-CoV-2, an infectious agent behind the ongoing COVID-19 pandemic, induces high levels of cytokines such as IL-1, IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ etc in infected individuals which contribute towards the underlying disease patho-physiology. Nonetheless, exact association and contribution of every cytokine towards COVID-19 pathology remains poorly understood. Delineation of the role of the cytokines during COVID-19 holds the key of efficient patient management in clinics. This study performed a comprehensive meta-analysis to establish association between induced cytokines and COVID-19 disease severity to help in prognosis and clinical care. Main methods: Scientific literature was searched to identify 13 cytokines (IL-1β, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-17, TNF-α and IFN-γ) from 18 clinical studies. Standardized mean difference (SMD) for selected 6 cytokines IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ between severe and non-severe COVID-19 patient groups were summarized using random effects model. A classifier was built using logistic regression model with cytokines having significant SMD as covariates. Key findings: Out of 13 cytokines, IL-6 and IL-10 showed statistically significant SMD across the studies synthesized. Classifier with mean values of both IL-6 and IL-10 as covariates performed well with accuracy of ~ 92% that was significantly higher than accuracy reported in literature with IL-6 and IL-10 as individual covariates. Significance: Simple panel proposed by us with only two cytokine markers can be used as predictors for fast diagnosis of patients with higher risk of COVID-19 disease deterioration and thus can be managed well for a favourable prognosis.

RR:C19 Evidence Scale rating by reviewer:

  • Strong. The main study claims are very well-justified by the data and analytic methods used. There is little room for doubt that the study produced has very similar results and conclusions as compared with the hypothetical ideal study. The study’s main claims should be considered conclusive and actionable without reservation.



SARS-CoV-2 infection associated cytokine storm is considered a major cause for the mortality of COVID-19 patients. Many clinical studies have measured circulating cytokine levels in COVID-19 patients with different severity and reported strong correlation between levels of inflammatory cytokines such as IL-6 and poor prognosis of the infected patients. Furthermore, recent meta-analyses published by other groups also showed strong correlations between inflammatory cytokine levels including IL-6 and IL-10 and COVID-19 disease severity.

The manuscript by Dhar et al. presented results from a meta-analysis and regression on the levels of 13 circulating cytokines in 1,242 non-severe and 915 severe COVID-19 patients from 18 clinical studies. The authors used random effects model to analyze standardized mean difference (SMD) of 6 cytokines (IL-2, IL-4, IL-6, IL-10, TNF- and IFN-) and logistic regression model to build a classifier with cytokines with significant SMD as covariates. They showed that IL-6 and IL-10 have significant SMD across the included studies while the other four cytokines did not. Furthermore, the authors demonstrated that a classifier using the mean values of both IL-6 and IL-10 as covariates has an overall accuracy of 91.7% and the area under the ROC curve (AUC) of 0.957 in separating severe versus non-severe COVID-19 patients, notably higher than the accuracy and AUC values afforded by single IL-6 or IL-10 value in this report and also other individual studies. The conclusion is justified by the data and analytic methods used. The results provided more reliable evidences than individual studies.

This meta-analysis study is clinically significant in two aspects. First, the impressive accuracy and AUC derived from combined IL-6/IL-10 mean values provide a potential prognostic tool to classify COVID-19 patients based on circulating cytokine levels. A prognostic tool accurately predicting COVID-19 progression into severe status is essential for therapeutic intervention to reduce patient mortality. Second, the results should draw more attention to the critical role of IL-10 in COVID-19 pathogenesis. The role of IL-6 in cytokine storm is well-established and its clinical significance has been verified by the effective treatment of cytokine storm in blood cancer patients receiving engineered chimeric antigen receptor T cell therapy with the anti-IL-6R monoclonal antibody tocilizumab. However, a recent randomized, double-blind phase III trial testing the clinical efficacy of tocilizumab in hospitalized COVID-19 patients by Roche failed to demonstrate a significant reduction in mortality. This phase III trial results suggest additional cytokine(s) among the ~20 elevated cytokines/chemokines during a cytokine storm in COVID-19 patients may play pathological roles and need to be targeted to reduce mortality. This study suggests that IL-10 may be an important therapeutic target for cytokine storm in COVID-19 patients.

The manuscript could be improved by further refining the analysis and discussion. First, the study included reports from one geographic area. The conclusion can be strengthened by including clinical reports on COVID-19 patients from distinct geographic locations worldwide. Second, an important promise for the presented classifier is to predict COVID-19 progression based on on-admission cytokine levels. Therefore, the relation between the timing of the blood samples taken in relative to disease course of the included COVID-19 patients and the predicting power of IL-6/IL-10 values need to be analyzed. Third, the authors had missed some of the important literature on the clinical effect of recombinant IL-10 in human patients and this may lead to some level of misunderstanding on the role of IL-10 in COVID-19 pathogenesis in their discussion. Recombinant IL-10 enhanced production of proinflammatory cytokine production in chronic active Crohn’s disease patients (Tilg, H. et al. 2002; Gut 50:191). Administration of pegylated recombinant IL-10 into cancer patients induced systemic immune activation and tumor control (Naing, A. et al. 2016; J Clin Oncol 34:3562 and 2018; Cancer Cell 34:775). Furthermore, rIL-10 promoted inflammation in healthy human subjects with lipopolysaccharide injection-caused endotoxemia (Lauw, F.N. et al. 2000;J Immunol 165:2783). Results from these human studies have clearly shown that rIL-10 functions as a potent immune activating/proinflammatory cytokine and the role of the elevated IL-10 in severe COVID-19 patients is likely consistent with such a proinflammatory role during pathogenesis leading to mortality.

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