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With great interest, we have read the recent article entitled ‘Prevalence and clinical outcomes of COVID-19 in patients with autoimmune diseases: a systematic review and meta-analysis’, which is published online in Annals of the Rheumatic Diseases.1 In this paper, Akiyama et al performed a meta-analysis to investigate the prevalence and clinical outcomes of coronavirus disease 2019 (COVID-19) in patients with autoimmune diseases.1 The authors observed that there was no significant difference in death between COVID-19 patients with autoimmune diseases and those without (odds ratio (OR)=0.545, 95% confidence interval (CI): 0.081 to 3.682).1 It is an extremely interesting study. But, their findings were based on only five published studies. Up to now, a considerable number of studies on this topic are emerging. Therefore, the association between autoimmune diseases and COVID-19 mortality is needed to be clarified on the basis of updated data by a quantitative meta-analysis.
We performed this meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines.2 A comprehensive literature search was performed in electronic databases including PubMed, Web of Science and EMBASE to identify eligible studies from 1 January 2020 to 23 December 2020 using the following keywords: ‘coronavirus disease 2019’ or ‘COVID-19’ or ‘severe acute respiratory syndrome coronavirus-2’ or ‘SARS-CoV-2’ and ‘autoimmune diseases’ or ‘rheumatic diseases’ or ‘inflammatory bowel disease’ or ‘psoriasis’ or ‘systemic lupus erythematosus’ and ‘mortality’ or ‘death’ or ‘fatality’ or ‘non-survivor’ or ‘deceased’. The reference lists of relevant literatures were also reviewed to identify missing studies. We included articles investigating the association between autoimmune diseases and COVID-19 mortality. Duplicated publications, case reports, reviews, comments, protocols and corrections were excluded.
Two investigators (HY and JX) independently extracted relevant information from the eligible studies. Disagreements were resolved through discussions with the third investigator (YW). We used I2 statistic to assess heterogeneity between studies.3 A fixed effects model was applied to estimate the pooled effect size and 95% CI in the absence of heterogeneity (I2 <50%), otherwise, a random effects model was used if there was significant heterogeneity (I2 >50%).4 5 Sensitivity analysis was performed to assess the stability of the results.6 Publication bias was assessed by Begg’s test and Egger’s test.7–9 The data analyses were performed by R software (V.3.6.3). The level of significance was set at p<0.05.
The flow diagram outlining the literature search process is shown in online supplemental figure S1. A total of 50 eligible studies with 307,827 patients with COVID-19 were included in this meta-analysis. The baseline characteristics of the included studies are summarised in table 1. Our meta-analysis demonstrated that COVID-19 patients with autoimmune diseases had a significantly increased risk of mortality compared with those without (pooled effect size=1.30, 95% CI: 1.14 to 1.48, p<0.001; figure 1). When we restricted autoimmune diseases to rheumatic disease, the significant association between rheumatic disease and an increased risk of COVID-19 mortality was still announced (pooled effect size=1.44, 95% CI: 1.22 to 1.70, p<0.001; online supplemental figure S2). Consistent results were observed in the subgroup analyses by sample size (pooled effect size=1.36, 95% CI: 1.13 to 1.65 for ≥500 and pooled effect size=1.26, 95% CI: 1.08 to 1.47 for <500, online supplemental figure S3), age (pooled effect size=1.18, 95% CI: 1.04 to 1.33 for ≥60 years old and pooled effect size=2.03, 95% CI: 1.60 to 2.58 for <60 years old, online supplemental figure S4) and male percentage (pooled effect size=1.31, 95% CI: 1.12 to 1.54 for ≥60% and pooled effect size=1.31, 95% CI: 1.10 to 1.57 for <60%, online supplemental figure S5). Subgroup analysis by location indicated that the significant association between autoimmune diseases and COVID-19 mortality existed in the USA (pooled effect size=1.42, 95% CI: 1.09 to 1.85) and Europe (pooled effect size=1.26, 95% CI: 1.05 to 1.53), but not in Asia (pooled effect size=1.19, 95% CI: 0.83 to 1.69, online supplemental figure S6). Sensitivity analysis exhibited that our results were stable and robust (online supplemental figure S7). No publication bias was observed in Begg’s test (p=0.332, online supplemental figure S8A) and Egger’s test (p=0.685, online supplemental figure S8B).
The current study findings do have several limitations. First, this study was based on crude effect estimates, it has been reported that age, gender and certain pre-existing comorbidities (such as hypertension, diabetes mellitus, cerebrovascular disease, chronic obstructive pulmonary disease and cardiovascular disease, etc.) 10–15 have significant effects on the clinical outcomes of patients with COVID-19. Therefore, further well-designed studies based on adjusted effect estimates should be performed to validate our results. Second, this present study did not address the effects of medications on the association between autoimmune diseases and COVID-19 mortality, which should be investigated in the future. Third, most of the included studies came from Europe and the USA, thus the conclusions drawn from this study should be cautiously extrapolated to other regions.
In conclusion, our updated meta-analysis demonstrates that autoimmune diseases are significantly associated with an increased risk of COVID-19 mortality, which might provide new insight into the association between autoimmune diseases and COVID-19 mortality. We hope that the updated data will contribute to more accurate elaboration and substantiation of the findings reported by Akiyama et al.1
We would like to thank Ying Wang, Xuan Liang, Wenwei Xiao, Hongjie Hou, Peihua Zhang, Jian Wu and Yang Li (all are from Department of Epidemiology, School of Public Health, Zhengzhou University) for their kind help in searching articles and collecting data, and valuable suggestions for data analysis.
Contributors YW and HY designed the study. JX and LS performed literature search. HY and JX performed data extraction. JX, HY, LS and GD performed statistical analyses. HY, JX and YW wrote and reviewed the manuscript. All the authors approved the final version of the manuscript.
Funding This study was supported by grants from the National Natural Science Foundation of China (grant number 81973105), Key Scientific Research Project of Henan Institution of Higher Education (grant number 21A330008), the National Science and Technology Major Projects of China (grant number 2018ZX10301407) and Joint Construction Project of Henan Medical Science and Technology Research Plan (grant number LHGJ20190679).
Disclaimer The funders have no role in the data collection, data analysis, preparation of manuscript and decision to submission.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; internally peer reviewed.
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