# Severity and Mortality Associated with Steroid Use among Patients with COVID-19: A Systematic Review and Meta-Analysis

Authors: Tamiru Sahilu; Tadesse Sheleme; Tsegaye Melaku
Journal: Interdisciplinary Perspectives on Infectious Diseases
 (2021)

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## Abstract

Background. There are controversial suggestions about steroid use to treat patients infected with COVID-19. Conclusive evidence regarding the use of steroids to treat COVID-19 is still lacking. This meta-analysis aimed to determine the mortality and severity associated with corticosteroid therapy compared to noncorticosteroid treatment in patients with COVID-19. Methods. The information was collected from electronic databases: PubMed, CINAHL, the Cochrane Library, clinicaltrials.gov, and Google scholar through January 30, 2021. Risk ratios (RRs) with 95% confidence intervals (CIs) were performed using random effect models. Endnote citation manager software version X9 for Windows was utilized to collect and organize search outcomes (into relevant and irrelevant studies) and to remove duplicate articles. Results. Thirty-two studies were included in the meta-analysis, including 14,659 COVID-19 patients. No significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.95; 95% CI: 0.80–1.13; p = 0.57). There was no significant reduction in mortality in critically ill COVID-19 patients treated with corticosteroid (RR = 0.89; 95% CI: 0.62–1.27; p = 0.52). Significant differences were observed in severe disease conditions between the steroid and nonsteroid treatment groups (RR = 1.10; 95% CI, 1.03–1.19, p = 0.007). Conclusion. There was no significant difference in all-cause mortality between the steroid and nonsteroid treatment users’ of COVID-19 patients. There was no significant reduction of all-cause mortality in critically ill COVID-19 patients treated with corticosteroids.


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## Body

## 1. Background

Coronavirus disease-19 (COVID-19) was first identified at the end of 2019 in Wuhan City, China. It rapidly spread in China and other countries throughout the world [1, 2]. In March 2020, the World Health Organization characterized the disease as pandemic [3]. As of May 21, 2020, more than five million confirmed cases have been documented and several death cases reported globally. It is affecting 213 countries and territories around the world and 2 international conveyances [4]. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is identified as the cause of COVID-19 [5].Currently, there is no drug confirmed by clinical trial to prevent or treat COVID-19. However, more than 300 active clinical treatment trials are under investigation [6]. Drugs that are already marketed for other conditions are being off-label used. For example, antimalarial medications chloroquine and hydroxychloroquine are widely used to treat COVID-19 [7]. A multinational registry analysis debunked the benefit of hydroxychloroquine or chloroquine when used alone or with a macrolide. The finding of the study showed that each of these regimens was associated with decreased in-hospital survival and an increased frequency of ventricular arrhythmias when used for the treatment of COVID-19 [8]. Remdesivir is another drug being used as a promising option for treating COVID-19 based on laboratory experiments [9].Corticosteroids were widely used to treat severe acute respiratory syndrome coronavirus-1(SARS-CoV-1) and Middle East respiratory syndrome coronavirus (MERS) during their outbreaks and are being used in patients with COVID-2019 [10]. Up to 70% of critically ill patients are receiving systemic corticosteroids. It is identified that patients treated with a corticosteroid had more clinical symptoms, a higher inflammation index, and more abnormalities on chest computed tomography [11]. A study showed that the use of high-dose corticosteroids increases the risk of death in patients with severe COVID-19 [12], indicating several controversial issues about the use of the steroid to treat patients infected with COVID-19. It is suggested that available evidence does not endorse the use of a steroid for COVID-19 patients, which may cause several side effects [13]. However, it is believed that short-term glucocorticoid therapy with small- or medium-dose could be beneficial for patients with severe conditions [14]. According to the World Health Organization (WHO) guidelines recommendation, glucocorticoids should only be used under clinical trial conditions [15]. Conclusive evidence regarding the use of the steroid to treat COVID-19 is still lacking. Therefore, this study aims to summarize the current evidence of the severity and mortality associated with steroid therapy for patients with COVID-19 which will support us in making the best decision in the management of the COVID-19.


## 2. Methods

### 2.1. Study Design

Analyses were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [16]. This study was registered in PROSPERO with registration number CRD42020185773.


### 2.2. Search Strategy

The information was collected from electronic databases: PubMed, CINAHL, the Cochrane Library,clinicaltrial.gov, and Google scholar. There was no limitation applied to the language. The reference list of all identified articles was searched for additional studies. Then, an extensive list of search terms was prepared by the analysis of title, abstract, and keywords of retrieved articles. A full-scale search of databases in PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, clinicaltrial.gov, and Google scholar from inception to January 30, 2021, was performed. No language restriction was imposed during the identification of studies. Flow diagram was used to summarize the number of studies identified, screened, excluded, and finally included in the study.The search terms used were ((“covid 19” [All Fields] OR “covid 19” [MeSH Terms] OR “covid 19 vaccines” [All Fields] OR “covid 19 vaccines” [MeSH Terms] OR “covid 19 serotherapy” [All Fields] OR “covid 19 serotherapy” [Supplementary Concept] OR “covid 19 nucleic acid testing” [All Fields] OR “covid 19 nucleic acid testing” [MeSH Terms] OR “covid 19 serological testing” [All Fields] OR “covid 19 serological testing” [MeSH Terms] OR “covid 19 testing” [All Fields] OR “covid 19 testing” [MeSH Terms] OR “sars cov 2” [All Fields] OR “sars cov 2” [MeSH Terms] OR “severe acute respiratory syndrome coronavirus 2” [All Fields] OR “ncov” [All Fields] OR “2019 ncov” [All Fields] OR ((“coronavirus” [MeSH Terms] OR “coronavirus” [All Fields] OR “cov” [All Fields]) AND steroidal” [All Fields] OR “steroidals” [All Fields] OR “steroidic” [All Fields] OR “steroids” [MeSH Terms] OR “steroids” [All Fields] OR “steroid” [All Fields]) AND (“mortality” [MeSH Terms] OR “mortality” [All Fields] OR “mortalities” [All Fields] OR “mortality” [MeSH Subheading]) AND (“cohort studies” [MeSH Terms] OR (“cohort” [All Fields] AND “studies” [All Fields]) OR “cohort studies” [All Fields] OR (“cohort” [All Fields] AND “study” [All Fields]) OR “cohort study” [All Fields])) NOT (“review” [Publication Type] OR “review literature as topic” [MeSH Terms] OR “review” [All Fields]).


### 2.3. Study Selection

Two reviewers independently carried out a literature search and examined relevant studies and sequentially screened their titles and abstracts for eligibility. The full texts of potentially eligible studies were retrieved. Disagreements were solved in a discussion. A screening guide was used to ensure that all review authors reliably apply the selection criteria.


### 2.4. Inclusion and Exclusion Criteria

Randomized controlled trials (RCTs), observational studies, prospective and retrospective comparative cohort studies, and case-control studies were eligible for the review. The review considered all articles comparing corticosteroid with noncorticosteroid treatment for patients with the diagnosis of COVID-19. Nonhuman studies and studies that did not report mortality and severity data were excluded from the review. The outcome considered was mortality, death within the hospital (all-cause mortality) of COVID 19 patients. The other outcome studied was the number of severe cases in the two groups (corticosteroid versus noncorticosteroid treatment groups).


### 2.5. Methodological Quality Assessment

Selected papers were assessed by two independent reviewers for methodological validity before inclusion in the review. Observational studies were assessed using Newcastle–Ottawa Scale (NOS), which consists of three domains: (1) subject selection, (2) comparability of the study groups, and (3) assessment of outcome(s). A score of 0–9 was allocated to each study. A standardized Cochrane risk of bias tool was used for the randomized controlled trial (RCT). Any disagreements that arise between the reviewers were resolved through discussion.


### 2.6. Data Extraction

Two reviewers independently extracted data from the studies using a predesigned format prepared. Data that were extracted include first author, a region of study, included population, study design, sample size, comparator group, patient status, age, gender, interventions, mortality, and severity. Severe cases were characterized as patients admitted to ICU or on invasive mechanical ventilation.


### 2.7. Data Analysis and Statistical Methods

To perform a meta-analysis, Review Manager 5.4 (Copenhagen: The Cochrane Collaboration, 2014) was used. The outcome variables were calculated using the Mantel Haenszel formula. Risk ratios (RRs) were reported with 95% confidence intervals (CIs) for the variables. Thep value was two-tailed, and the statistical significance was set at ≤0.05. Heterogeneity was assessed with the Q-statistic test and the I2 test. The I2 statistic measured the percentage of total variation across the studies due to clinical or methodological heterogeneity instead of chance. The significant Q statistics (p < 0.05) indicated heterogeneity across the studies; thus, a random effect model was utilized. Substantial heterogeneity was represented by I2 for >50%.


## 2.1. Study Design

Analyses were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [16]. This study was registered in PROSPERO with registration number CRD42020185773.


## 2.2. Search Strategy

The information was collected from electronic databases: PubMed, CINAHL, the Cochrane Library,clinicaltrial.gov, and Google scholar. There was no limitation applied to the language. The reference list of all identified articles was searched for additional studies. Then, an extensive list of search terms was prepared by the analysis of title, abstract, and keywords of retrieved articles. A full-scale search of databases in PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, clinicaltrial.gov, and Google scholar from inception to January 30, 2021, was performed. No language restriction was imposed during the identification of studies. Flow diagram was used to summarize the number of studies identified, screened, excluded, and finally included in the study.The search terms used were ((“covid 19” [All Fields] OR “covid 19” [MeSH Terms] OR “covid 19 vaccines” [All Fields] OR “covid 19 vaccines” [MeSH Terms] OR “covid 19 serotherapy” [All Fields] OR “covid 19 serotherapy” [Supplementary Concept] OR “covid 19 nucleic acid testing” [All Fields] OR “covid 19 nucleic acid testing” [MeSH Terms] OR “covid 19 serological testing” [All Fields] OR “covid 19 serological testing” [MeSH Terms] OR “covid 19 testing” [All Fields] OR “covid 19 testing” [MeSH Terms] OR “sars cov 2” [All Fields] OR “sars cov 2” [MeSH Terms] OR “severe acute respiratory syndrome coronavirus 2” [All Fields] OR “ncov” [All Fields] OR “2019 ncov” [All Fields] OR ((“coronavirus” [MeSH Terms] OR “coronavirus” [All Fields] OR “cov” [All Fields]) AND steroidal” [All Fields] OR “steroidals” [All Fields] OR “steroidic” [All Fields] OR “steroids” [MeSH Terms] OR “steroids” [All Fields] OR “steroid” [All Fields]) AND (“mortality” [MeSH Terms] OR “mortality” [All Fields] OR “mortalities” [All Fields] OR “mortality” [MeSH Subheading]) AND (“cohort studies” [MeSH Terms] OR (“cohort” [All Fields] AND “studies” [All Fields]) OR “cohort studies” [All Fields] OR (“cohort” [All Fields] AND “study” [All Fields]) OR “cohort study” [All Fields])) NOT (“review” [Publication Type] OR “review literature as topic” [MeSH Terms] OR “review” [All Fields]).


## 2.3. Study Selection

Two reviewers independently carried out a literature search and examined relevant studies and sequentially screened their titles and abstracts for eligibility. The full texts of potentially eligible studies were retrieved. Disagreements were solved in a discussion. A screening guide was used to ensure that all review authors reliably apply the selection criteria.


## 2.4. Inclusion and Exclusion Criteria

Randomized controlled trials (RCTs), observational studies, prospective and retrospective comparative cohort studies, and case-control studies were eligible for the review. The review considered all articles comparing corticosteroid with noncorticosteroid treatment for patients with the diagnosis of COVID-19. Nonhuman studies and studies that did not report mortality and severity data were excluded from the review. The outcome considered was mortality, death within the hospital (all-cause mortality) of COVID 19 patients. The other outcome studied was the number of severe cases in the two groups (corticosteroid versus noncorticosteroid treatment groups).


## 2.5. Methodological Quality Assessment

Selected papers were assessed by two independent reviewers for methodological validity before inclusion in the review. Observational studies were assessed using Newcastle–Ottawa Scale (NOS), which consists of three domains: (1) subject selection, (2) comparability of the study groups, and (3) assessment of outcome(s). A score of 0–9 was allocated to each study. A standardized Cochrane risk of bias tool was used for the randomized controlled trial (RCT). Any disagreements that arise between the reviewers were resolved through discussion.


## 2.6. Data Extraction

Two reviewers independently extracted data from the studies using a predesigned format prepared. Data that were extracted include first author, a region of study, included population, study design, sample size, comparator group, patient status, age, gender, interventions, mortality, and severity. Severe cases were characterized as patients admitted to ICU or on invasive mechanical ventilation.


## 2.7. Data Analysis and Statistical Methods

To perform a meta-analysis, Review Manager 5.4 (Copenhagen: The Cochrane Collaboration, 2014) was used. The outcome variables were calculated using the Mantel Haenszel formula. Risk ratios (RRs) were reported with 95% confidence intervals (CIs) for the variables. Thep value was two-tailed, and the statistical significance was set at ≤0.05. Heterogeneity was assessed with the Q-statistic test and the I2 test. The I2 statistic measured the percentage of total variation across the studies due to clinical or methodological heterogeneity instead of chance. The significant Q statistics (p < 0.05) indicated heterogeneity across the studies; thus, a random effect model was utilized. Substantial heterogeneity was represented by I2 for >50%.


## 3. Results and Discussion

The search returned a total of 1419 (PubMed: 85, Google Scholar: 1290, clinicaltrials.gov: 24, Cochrane Library: 1, and other sources: 19) citations, of which 40 were duplicates. According to the exclusion criteria, 1292 citations were excluded after the title and abstract screening. Figure1 shows the study selection processes.Figure 1
PRISMA study flow diagram.


### 3.1. Characteristics of the Included Studies

The present meta-analysis included 28 observational studies [12, 17–43] and 4 RCTs [44–47]. These studies included 14,659 patients with the diagnosis of COVID-19 who received corticosteroids (5,830 patients) or noncorticosteroids (8,829 patients). Tables 1 and 2 list the characteristics of the included studies. All eligible studies were published in 2020/21. Individual assessment of the risk of bias was presented in Table 3.Table 1
Characteristics of included studies.
S.NoAuthorsStudy typeSample sizeNumber of controlPatient statusCountryFollow-up period1Wang et al. [19]Retrospective study4620COVID-19 with pneumoniaWuhan Union Hospital, ChinaJanuary 20 to February 25, 20202Fadel et al. [17]Multicenter quasi-experimental study21381COVID-19Five hospitals in Michigan, USAMarch 12, 2020 through March 27, 20203Wu et al. [21]Retrospective cohort study201139COVID-19 with pneumoniaWuhan Jinyintan Hospital in ChinaDecember 25, 2019, to January 26, 20204Li et al. [12]Ambispective cohort study548207COVID-19Tongji Hospital, ChinaJanuary 26, to March 3, 2020.5Zhou et al. [23]Multicenter, retrospective cohort study191134COVID-19Wuhan, ChinaDec 29, 2019, to Jan 31, 20206Shang et al. [18]Multicenter, retrospective, observational study416220COVID-19Hubei province, ChinaDec 27, 2019, to Feb 17, 20207Yang et al. [22]Retrospective observational study5222SARS-CoV-2 pneumoniaWuhan, ChinaDecember, 2019, to Jan 26, 20208Huang et al. [24]Prospective cohort study4132COVID-19Wuhan, ChinaDec 16, 2019, to Jan 2, 20209Guan et al. [27]Retrospective cohort study1099895COVID-19ChinaDecember 11, 2019, to January 31, 2020.10Zhao et al. [26]Retrospective cohort study9112COVID-19Jingzhou Central Hospital, ChinaJanuary 16, 2020, to February 10, 2020.11Ling et al. [25]Retrospective cohort study6661COVID-19Shanghai, ChinaJanuary 20, to February 10, 202012Horby et al. [44]Randomized controlled trial64254321COVID-19United KingdomMarch 9, to June 8, 202013Angus et al. [45]Randomized controlled trial384101COVID-19REMAP-CAP multicenter (Australia, Canada, France, Ireland, The Netherlands, New Zealand, the United Kingdom, and the United States)March 9 to August 12, 202014Borie et al. [28]Cohort study17163COVID-19ParisMarch 27 to April 10, 202015Dequin et al. [46]Randomized controlled trial14973Critically Ill patients with COVID-19FranceMarch 7 to June 29, 202016Falcone et al. [43]Prospective observational study315174COVID-19 and pneumoniaUniversity Hospital of PisaMarch 4–April 30, 202017Fernández-Cruz et al. [29]Retrospective controlled cohort study46367COVID-19 and pneumoniaSpain4 March 2020 to 7 April 202018Jeronimo et al. [47]Randomized controlled trial393199COVID-19Brazil18 April to 16 June 202019Krishnan et al. [30]Retrospective observational study152136COVID-19 and pneumoniaUSAMarch 10, to April 15, 202020Li et al. 2020 [31]Multicenter, retrospective study294111Critically ill COVID-19 patientsHubei, ChinaBetween December 30, 2019 and February 19, 202021Papamanoli et al. [32]Retrospective cohort447294severe COVID-19 pneumoniaNew York, USA1 March to 15 April 202022Tomazini et al. [48]Randomized controlled trial299148Acute respiratory distress syndrome and COVID-19BrazilApril 17 to July 21, 202023You et al. [33]Retrospective cohort study343225COVID-19ChinaFebruary 1 to March 31, 202024Rodríguez-Baño et al. [34]Retrospective cohort study778583COVID-19SpainFebruary 2 to March 31, 202025Ma et al. [35]Multicenter retrospective cohort study7225COVID-19ChinaJanuary 2020 to March 202026Lu et al. [36]Retrospective cohort study6231Critically ill COVID-19ChinaJanuary 25 to February 25, 202027Cao et al. [37]Retrospective cohort study10251COVID-19ChinaJanuary 3 and February 1, 202028Nelson et al. [38]Retrospective cohort study11769COVID-19 pneumoniaUSAMarch 1, 2020 and April 12, 202029Bani-Sadr et al. [39]Prospective cohort study25785COVID-19 pneumoniaFrance3 March 2020 and 14 April 202030Salton et al. [40]Multicenter observational study17390severe COVID-19 pneumoniaItalyFebruary 27 to May 21, 202031Mikulska et al. [41]Observational single-center study19666COVID-19 pneumoniaItalyNR32Majmundar et al. [42]Retrospective cohort study205145COVID-19 pneumoniaUSAMarch 15 to April 30, 2020Table 2
Characteristics of included studies.
S. NoAuthorsMedian age (IQR) in yearsGenderInterventionNo. of patientsMortalitySevere casesControl groupIntervention groupControl groupIntervention group1Wang et al. [19]54 (48–64)26 (57%) malesMethylprednisolone (n = 26)12NRNR2Fadel et al. [17]62 (51–62)109 (51.2%) maleMethylprednisolone (n = 132)211821273Wu et al. [21]51 (43–60)128 (63.7%) menMethylprednisolone (n = 62)2123NRNR4Li et al. [12]60 (48–69)279 (50.9%) maleSystemic corticosteroids (n = 341)NRNR731965Zhou et al. [23]56 (46–67)Male 119 (62%)Corticosteroids (n = 57)2826NRNR6Shang et al. [18]49 (36–61)197 (47%) malesCorticosteroid therapy (n = 196)84362777Yang et al. [22]59·735 (67%) malesGlucocorticoids (n = 30)161622308Huang et al. [24]49 (41–58) years30 [73%] malesUse of corticosteroid (n = 9)NRNR769Guan et al. [27]47 years639 malesSystemic glucocorticoids(n = 204)105967710Zhao et al. [26]46 years49 malesGlucocorticoid (n = 79)1152511Ling et al. [25]44 (34–62) years38 malesGlucocorticoid (n = 5)00NRNR12Horby et al. [44]66.1 years4088 malesDexamethasone (n = 2104)106545468332413Angus et al. [45]Mean age, 60 years29% femaleHydrocortisone (n = 283)337810128314Borie et al. [28]Median (IQR): 67.1 (56.7–78.1)Female 48 (28.1%)Methyl-prednisolone (n = 108)25326310815Dequin et al. [46]Mean age, 62.2 years30.2% womenHydrocortisone (n = 76)2011737616Falcone et al. [43]Median age was 70 (IQR, 57–80)(76.2%) malesSteroids (n = 141)4327NRNR17Fernández-Cruz et al. [29]Mean age 66.75 years317 malesSteroids (n = 396)165505818Jeronimo et al. [47]Mean age (SD) 55 ± 15 yrs139 femalesMethylprednisolone (n = 194)7672NRNR19Krishnan et al. [30]68 years (IQR 58–75)95 malesOral steroidsn = 1682101361620Li et al. [31]66 yrs (56–75)197 (67%) malesCorticosteroids,n = 183499711118321Papamanoli et al. [32]Mean age 61.5 yrsFemales 156Methylprednisolone,n = 1531467129415322Tomazini et al. [48]Mean age 61.4 yrsFemales 112Dexamethasone (n = 151)918514815123You et al. [33]Mean age 53.8Female 157Methylprednisolone (n = 118)11495824Rodríguez-Baño et al. [34]Age 71 yrsFemale 226Corticosteroids (n = 195)6230NRNR25Ma et al. [35]Age 60 (13.8) yrsFemale 32 (44%)Corticosteroid group (n = 47)22254726Lu et al. [36]57 (50–69) yrsMale 32Steroid (n = 31)512313127Cao et al. [37]Age, years 54(37–67)Female 49Methylprednisolone Sodium (n = 51)611NRNR28Nelson et al. [38]Age 61.5 (46–69)Male 80Methylprednisolonen = 482915694829Bani-Sadr et al. [39]Age 71 yrsMale 135Corticosteroidsn = 172173112930Salton et al. [40]Age 65.75 yrsMale 120Methylprednisolone (n = 83)216908331Mikulska et al. [41]Age mean 67.5 yrsMale 132Methylprednisolone (n = 130)2214NRNR32Majmundar et al. [42]Age, mean 57.61Male 153Corticosteroids (N = 60)34800NR: not reported.Table 3
Methodological quality assessment.
Newcastle–Ottawa scale (NOS)StudiesSelectionComparabilityOutcomeQuality scoreABcdefghFadel et al. [17]∗∗∗∗∗∗∗∗8Guan et al. [27]∗∗∗∗∗∗∗∗∗9Huang et al. [24]∗∗∗∗∗∗∗∗8Li et al. [12]∗∗∗∗∗∗6Ling et al. [25]∗∗∗∗∗∗6Shang et al. [18]∗∗∗∗∗∗6Yang et al. [22]∗∗∗∗∗∗6Wang et al. [19]∗∗∗∗∗∗6Wu et al. [21]∗∗∗∗∗∗∗7Zhao et al. [26]∗∗∗∗∗∗6Zhou et al. [23]∗∗∗∗∗∗∗7Borie et al. [28]∗∗∗∗∗∗6Falcone et al. [43]∗∗∗∗∗∗∗7Fernández-Cruz et al. [29]∗∗∗∗∗∗∗7Krishnan et al. [30]∗∗∗∗∗∗6Li et al. [31]∗∗∗∗∗∗6Papamanoli et al. [32]∗∗∗∗∗∗∗7You et al. [33]∗∗∗∗∗∗6Rodríguez-Baño et al. [34]∗∗∗∗∗∗∗7Ma, Q et al. [35]∗∗∗∗∗∗∗7Lu et al. [36]∗∗∗∗∗∗∗7Cao et al. [37]∗∗∗∗∗∗6Nelson et al. [38]∗∗∗∗∗∗∗7Bani-Sadr et al. [39]∗∗∗∗∗∗6Salton et al. [40]∗∗∗∗∗∗∗7Mikulska et al. [41]∗∗∗∗∗∗6Majmundar et al. [42]∗∗∗∗∗∗∗7Cochrane risk of bias toolIJklmnHorby et al. [44]Low risk of biasLow risk of biasHigh risk of biasUnclear risk of biasLow risk of biasLow risk of biasAngus et al. [45]Low risk of biasLow risk of biasHigh risk of biasLow risk of biasLow risk of biasLow risk of biasDequin et al. [46]Low risk of biasHigh risk of biasHigh risk of biasLow risk of biasLow risk of biasLow risk of biasJeronimo et al. [47]Low risk of biasLow risk of biasHigh risk of biasLow risk of biasLow risk of biasLow risk of biasa: representativeness of the exposed cohort, b: selection of the nonexposed cohort, c: ascertainment of exposure, d: demonstration that the outcome of interest was not present at the start of the study, e: comparability of cohorts based on the design or analysis, f: assessment of outcome, g: follow-up long enough for outcomes to occur, h: adequacy of follow-up of the cohort; i: random sequence generation (selection bias), j: allocation concealment (selection bias), k: blinding of participants and personnel (performance bias), l: blinding of outcome assessment (detection bias), m: incomplete outcome data (attrition bias), n: selective reporting (reporting bias).


### 3.2. Mortality Associated with Steroid Use in Patients with COVID-19

In the 26 included studies [17–19, 21–23, 25–30, 32–35, 37–42, 44, 45, 47, 48] with 13,565 patients, there were no significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.95; 95% CI: 0.80–1.13; p = 0.57, I2 = 78%, p < 0.0001) (Figure 2). The sensitivity analysis showed that the exclusion of three studies [18, 21, 33] changed the above conclusion.Figure 2
Forest plot for mortality of COVID-19 patients taking steroids versus nonsteroids.


### 3.3. Mortality Associated with Steroid Use in Patients with Critically Ill COVID-19 Patients

In the 5 included studies [22, 31, 36, 44, 46] with 1,564 critically ill COVID-19 patients, there were no significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.89; 95% CI: 0.62–1.27; p = 0.52, I2 = 78%, p = 0.001) (Figure 3).Figure 3
Forest plot for mortality associated with steroid use in patients with critically ill COVID-19 patients.


### 3.4. Severity Associated with Steroid Use in Patients with COVID-19

Twenty-three studies reported the severity data of the COVID-19 patients. In the included studies [12, 17, 18, 22, 24, 26–33, 35, 36, 38–40, 42, 44–46, 48] with 12,473 patients, there were significant differences in severe disease condition between the steroid and nonsteroid treatment groups (RR = 1.10; 95% CI, 1.03–1.19, p = 0.007) (Figure 4). There was significant heterogeneity among the studies (I2 = 99% p < 0.001); the random-effects model was used.Figure 4
Forest plot for severe events of COVID-19 patients taking steroids versus nonsteroids.


### 3.5. Publication Bias

To assess the small-study effect and publication bias, the regression-based Egger’s test was performed. The funnel-plot analysis showed a symmetrical shape for mortality (Figure5), indicating no publication bias; Egger’s test indicated nonsignificant small-study effects (p = 0.570). The funnel-plot analysis showed asymmetrical shape for severe cases (Figure 6), indicating publication bias; Egger’s test indicated significant small-study effects for severe cases (p = 0.027).Figure 5
Funnel plot for mortality.Figure 6
Funnel plot for severe cases.


### 3.6. Sensitivity Analysis

Sensitivity analysis for between-study heterogeneity and analytical methods was performed to show the robustness of the finding. The analysis showed that the result was stable except for the exclusion of three studies [18, 21, 33] that changed the conclusion (Figure 7).Figure 7
Sensitivity analysis: forest plot for mortality of COVID-19 patients taking steroids versus nonsteroids.The rationale for the use of corticosteroids is to decrease the host inflammatory responses in the lungs, which may lead to acute lung injury and acute respiratory distress syndrome [6]. Because of the high amount of cytokines induced by COVID-19 infection, corticosteroids were used frequently for the treatment of patients with severe illness, for possible benefit by reducing inflammatory-induced lung injury [24]. There were potential harms and a lack of proven benefit for corticosteroid cautions against their routine use in patients with COVID-19 [6].Our analysis demonstrated that the mortality rate was comparable in COVID-19 patients treated with corticosteroids versus noncorticosteroids. However, in patients with critically ill COVID-19 patients, even though nonsignificant (RR = 0.89; 95% CI: 0.62–1.27;p = 0.52), a lower mortality rate in corticosteroid treatment groups was observed. Evidence suggests that cytokine storm, a hyperinflammatory state resembling secondary hemophagocytic lymphohistiocytosis (HLH), is a contributing factor in COVID-19-associated mortality [49].In our finding, there were no significant differences in mortality between the corticosteroid and noncorticosteroid treatment groups in critically ill COVID-19 patients. The initial clinical trial results from the United Kingdom (UK) showed that dexamethasone, a corticosteroid, can be lifesaving for patients who are critically ill with COVID-19. For patients on ventilators, the treatment was shown to reduce mortality by about one-third, and for patients requiring only oxygen, mortality was cut by about one-fifth, according to preliminary findings shared with the World Health Organization (WHO) [50].The most commonly invoked rationale for giving steroids in patients with severe COVID-19 is to modulate the destructive inflammatory immune response that occurs with advancing disease. The guidelines recommend against using corticosteroids to try to modulate the immune system in mechanically ventilated COVID-19 patients without acute respiratory distress syndrome (ARDS) but do recommend steroids in those with COVID-19 and ARDS [51]. Our finding demonstrates that there is an association between severe COVID-19 and corticosteroid therapy (RR = 1.10; 95% CI, 1.03–1.19, p = 0.007).A previous meta-analysis in persons with SARS-CoV-2, SARS-CoV, or MERS-CoV (Middle East respiratory syndrome coronavirus) infection indicated that corticosteroid did not significantly reduce the risk of death [52]. Another meta-analysis that included 5 studies indicated a lack of benefit of corticosteroid therapy on mortality in critically ill patients with COVID-19 [53]. In addition, a review that included 15 studies with coronavirus-infected patients (2 studies with COVID-19 patients) showed that corticosteroid treatment was associated with higher mortality and critical patients were more likely to require corticosteroids therapy [54].Some of the limitations of this meta-analysis are as follows: the included studies are retrospective cohort studies, there is a high degree of between-study heterogeneity, and mortality may be influenced by other therapeutic options.


## 3.1. Characteristics of the Included Studies

The present meta-analysis included 28 observational studies [12, 17–43] and 4 RCTs [44–47]. These studies included 14,659 patients with the diagnosis of COVID-19 who received corticosteroids (5,830 patients) or noncorticosteroids (8,829 patients). Tables 1 and 2 list the characteristics of the included studies. All eligible studies were published in 2020/21. Individual assessment of the risk of bias was presented in Table 3.Table 1
Characteristics of included studies.
S.NoAuthorsStudy typeSample sizeNumber of controlPatient statusCountryFollow-up period1Wang et al. [19]Retrospective study4620COVID-19 with pneumoniaWuhan Union Hospital, ChinaJanuary 20 to February 25, 20202Fadel et al. [17]Multicenter quasi-experimental study21381COVID-19Five hospitals in Michigan, USAMarch 12, 2020 through March 27, 20203Wu et al. [21]Retrospective cohort study201139COVID-19 with pneumoniaWuhan Jinyintan Hospital in ChinaDecember 25, 2019, to January 26, 20204Li et al. [12]Ambispective cohort study548207COVID-19Tongji Hospital, ChinaJanuary 26, to March 3, 2020.5Zhou et al. [23]Multicenter, retrospective cohort study191134COVID-19Wuhan, ChinaDec 29, 2019, to Jan 31, 20206Shang et al. [18]Multicenter, retrospective, observational study416220COVID-19Hubei province, ChinaDec 27, 2019, to Feb 17, 20207Yang et al. [22]Retrospective observational study5222SARS-CoV-2 pneumoniaWuhan, ChinaDecember, 2019, to Jan 26, 20208Huang et al. [24]Prospective cohort study4132COVID-19Wuhan, ChinaDec 16, 2019, to Jan 2, 20209Guan et al. [27]Retrospective cohort study1099895COVID-19ChinaDecember 11, 2019, to January 31, 2020.10Zhao et al. [26]Retrospective cohort study9112COVID-19Jingzhou Central Hospital, ChinaJanuary 16, 2020, to February 10, 2020.11Ling et al. [25]Retrospective cohort study6661COVID-19Shanghai, ChinaJanuary 20, to February 10, 202012Horby et al. [44]Randomized controlled trial64254321COVID-19United KingdomMarch 9, to June 8, 202013Angus et al. [45]Randomized controlled trial384101COVID-19REMAP-CAP multicenter (Australia, Canada, France, Ireland, The Netherlands, New Zealand, the United Kingdom, and the United States)March 9 to August 12, 202014Borie et al. [28]Cohort study17163COVID-19ParisMarch 27 to April 10, 202015Dequin et al. [46]Randomized controlled trial14973Critically Ill patients with COVID-19FranceMarch 7 to June 29, 202016Falcone et al. [43]Prospective observational study315174COVID-19 and pneumoniaUniversity Hospital of PisaMarch 4–April 30, 202017Fernández-Cruz et al. [29]Retrospective controlled cohort study46367COVID-19 and pneumoniaSpain4 March 2020 to 7 April 202018Jeronimo et al. [47]Randomized controlled trial393199COVID-19Brazil18 April to 16 June 202019Krishnan et al. [30]Retrospective observational study152136COVID-19 and pneumoniaUSAMarch 10, to April 15, 202020Li et al. 2020 [31]Multicenter, retrospective study294111Critically ill COVID-19 patientsHubei, ChinaBetween December 30, 2019 and February 19, 202021Papamanoli et al. [32]Retrospective cohort447294severe COVID-19 pneumoniaNew York, USA1 March to 15 April 202022Tomazini et al. [48]Randomized controlled trial299148Acute respiratory distress syndrome and COVID-19BrazilApril 17 to July 21, 202023You et al. [33]Retrospective cohort study343225COVID-19ChinaFebruary 1 to March 31, 202024Rodríguez-Baño et al. [34]Retrospective cohort study778583COVID-19SpainFebruary 2 to March 31, 202025Ma et al. [35]Multicenter retrospective cohort study7225COVID-19ChinaJanuary 2020 to March 202026Lu et al. [36]Retrospective cohort study6231Critically ill COVID-19ChinaJanuary 25 to February 25, 202027Cao et al. [37]Retrospective cohort study10251COVID-19ChinaJanuary 3 and February 1, 202028Nelson et al. [38]Retrospective cohort study11769COVID-19 pneumoniaUSAMarch 1, 2020 and April 12, 202029Bani-Sadr et al. [39]Prospective cohort study25785COVID-19 pneumoniaFrance3 March 2020 and 14 April 202030Salton et al. [40]Multicenter observational study17390severe COVID-19 pneumoniaItalyFebruary 27 to May 21, 202031Mikulska et al. [41]Observational single-center study19666COVID-19 pneumoniaItalyNR32Majmundar et al. [42]Retrospective cohort study205145COVID-19 pneumoniaUSAMarch 15 to April 30, 2020Table 2
Characteristics of included studies.
S. NoAuthorsMedian age (IQR) in yearsGenderInterventionNo. of patientsMortalitySevere casesControl groupIntervention groupControl groupIntervention group1Wang et al. [19]54 (48–64)26 (57%) malesMethylprednisolone (n = 26)12NRNR2Fadel et al. [17]62 (51–62)109 (51.2%) maleMethylprednisolone (n = 132)211821273Wu et al. [21]51 (43–60)128 (63.7%) menMethylprednisolone (n = 62)2123NRNR4Li et al. [12]60 (48–69)279 (50.9%) maleSystemic corticosteroids (n = 341)NRNR731965Zhou et al. [23]56 (46–67)Male 119 (62%)Corticosteroids (n = 57)2826NRNR6Shang et al. [18]49 (36–61)197 (47%) malesCorticosteroid therapy (n = 196)84362777Yang et al. [22]59·735 (67%) malesGlucocorticoids (n = 30)161622308Huang et al. [24]49 (41–58) years30 [73%] malesUse of corticosteroid (n = 9)NRNR769Guan et al. [27]47 years639 malesSystemic glucocorticoids(n = 204)105967710Zhao et al. [26]46 years49 malesGlucocorticoid (n = 79)1152511Ling et al. [25]44 (34–62) years38 malesGlucocorticoid (n = 5)00NRNR12Horby et al. [44]66.1 years4088 malesDexamethasone (n = 2104)106545468332413Angus et al. [45]Mean age, 60 years29% femaleHydrocortisone (n = 283)337810128314Borie et al. [28]Median (IQR): 67.1 (56.7–78.1)Female 48 (28.1%)Methyl-prednisolone (n = 108)25326310815Dequin et al. [46]Mean age, 62.2 years30.2% womenHydrocortisone (n = 76)2011737616Falcone et al. [43]Median age was 70 (IQR, 57–80)(76.2%) malesSteroids (n = 141)4327NRNR17Fernández-Cruz et al. [29]Mean age 66.75 years317 malesSteroids (n = 396)165505818Jeronimo et al. [47]Mean age (SD) 55 ± 15 yrs139 femalesMethylprednisolone (n = 194)7672NRNR19Krishnan et al. [30]68 years (IQR 58–75)95 malesOral steroidsn = 1682101361620Li et al. [31]66 yrs (56–75)197 (67%) malesCorticosteroids,n = 183499711118321Papamanoli et al. [32]Mean age 61.5 yrsFemales 156Methylprednisolone,n = 1531467129415322Tomazini et al. [48]Mean age 61.4 yrsFemales 112Dexamethasone (n = 151)918514815123You et al. [33]Mean age 53.8Female 157Methylprednisolone (n = 118)11495824Rodríguez-Baño et al. [34]Age 71 yrsFemale 226Corticosteroids (n = 195)6230NRNR25Ma et al. [35]Age 60 (13.8) yrsFemale 32 (44%)Corticosteroid group (n = 47)22254726Lu et al. [36]57 (50–69) yrsMale 32Steroid (n = 31)512313127Cao et al. [37]Age, years 54(37–67)Female 49Methylprednisolone Sodium (n = 51)611NRNR28Nelson et al. [38]Age 61.5 (46–69)Male 80Methylprednisolonen = 482915694829Bani-Sadr et al. [39]Age 71 yrsMale 135Corticosteroidsn = 172173112930Salton et al. [40]Age 65.75 yrsMale 120Methylprednisolone (n = 83)216908331Mikulska et al. [41]Age mean 67.5 yrsMale 132Methylprednisolone (n = 130)2214NRNR32Majmundar et al. [42]Age, mean 57.61Male 153Corticosteroids (N = 60)34800NR: not reported.Table 3
Methodological quality assessment.
Newcastle–Ottawa scale (NOS)StudiesSelectionComparabilityOutcomeQuality scoreABcdefghFadel et al. [17]∗∗∗∗∗∗∗∗8Guan et al. [27]∗∗∗∗∗∗∗∗∗9Huang et al. [24]∗∗∗∗∗∗∗∗8Li et al. [12]∗∗∗∗∗∗6Ling et al. [25]∗∗∗∗∗∗6Shang et al. [18]∗∗∗∗∗∗6Yang et al. [22]∗∗∗∗∗∗6Wang et al. [19]∗∗∗∗∗∗6Wu et al. [21]∗∗∗∗∗∗∗7Zhao et al. [26]∗∗∗∗∗∗6Zhou et al. [23]∗∗∗∗∗∗∗7Borie et al. [28]∗∗∗∗∗∗6Falcone et al. [43]∗∗∗∗∗∗∗7Fernández-Cruz et al. [29]∗∗∗∗∗∗∗7Krishnan et al. [30]∗∗∗∗∗∗6Li et al. [31]∗∗∗∗∗∗6Papamanoli et al. [32]∗∗∗∗∗∗∗7You et al. [33]∗∗∗∗∗∗6Rodríguez-Baño et al. [34]∗∗∗∗∗∗∗7Ma, Q et al. [35]∗∗∗∗∗∗∗7Lu et al. [36]∗∗∗∗∗∗∗7Cao et al. [37]∗∗∗∗∗∗6Nelson et al. [38]∗∗∗∗∗∗∗7Bani-Sadr et al. [39]∗∗∗∗∗∗6Salton et al. [40]∗∗∗∗∗∗∗7Mikulska et al. [41]∗∗∗∗∗∗6Majmundar et al. [42]∗∗∗∗∗∗∗7Cochrane risk of bias toolIJklmnHorby et al. [44]Low risk of biasLow risk of biasHigh risk of biasUnclear risk of biasLow risk of biasLow risk of biasAngus et al. [45]Low risk of biasLow risk of biasHigh risk of biasLow risk of biasLow risk of biasLow risk of biasDequin et al. [46]Low risk of biasHigh risk of biasHigh risk of biasLow risk of biasLow risk of biasLow risk of biasJeronimo et al. [47]Low risk of biasLow risk of biasHigh risk of biasLow risk of biasLow risk of biasLow risk of biasa: representativeness of the exposed cohort, b: selection of the nonexposed cohort, c: ascertainment of exposure, d: demonstration that the outcome of interest was not present at the start of the study, e: comparability of cohorts based on the design or analysis, f: assessment of outcome, g: follow-up long enough for outcomes to occur, h: adequacy of follow-up of the cohort; i: random sequence generation (selection bias), j: allocation concealment (selection bias), k: blinding of participants and personnel (performance bias), l: blinding of outcome assessment (detection bias), m: incomplete outcome data (attrition bias), n: selective reporting (reporting bias).


## 3.2. Mortality Associated with Steroid Use in Patients with COVID-19

In the 26 included studies [17–19, 21–23, 25–30, 32–35, 37–42, 44, 45, 47, 48] with 13,565 patients, there were no significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.95; 95% CI: 0.80–1.13; p = 0.57, I2 = 78%, p < 0.0001) (Figure 2). The sensitivity analysis showed that the exclusion of three studies [18, 21, 33] changed the above conclusion.Figure 2
Forest plot for mortality of COVID-19 patients taking steroids versus nonsteroids.


## 3.3. Mortality Associated with Steroid Use in Patients with Critically Ill COVID-19 Patients

In the 5 included studies [22, 31, 36, 44, 46] with 1,564 critically ill COVID-19 patients, there were no significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.89; 95% CI: 0.62–1.27; p = 0.52, I2 = 78%, p = 0.001) (Figure 3).Figure 3
Forest plot for mortality associated with steroid use in patients with critically ill COVID-19 patients.


## 3.4. Severity Associated with Steroid Use in Patients with COVID-19

Twenty-three studies reported the severity data of the COVID-19 patients. In the included studies [12, 17, 18, 22, 24, 26–33, 35, 36, 38–40, 42, 44–46, 48] with 12,473 patients, there were significant differences in severe disease condition between the steroid and nonsteroid treatment groups (RR = 1.10; 95% CI, 1.03–1.19, p = 0.007) (Figure 4). There was significant heterogeneity among the studies (I2 = 99% p < 0.001); the random-effects model was used.Figure 4
Forest plot for severe events of COVID-19 patients taking steroids versus nonsteroids.


## 3.5. Publication Bias

To assess the small-study effect and publication bias, the regression-based Egger’s test was performed. The funnel-plot analysis showed a symmetrical shape for mortality (Figure5), indicating no publication bias; Egger’s test indicated nonsignificant small-study effects (p = 0.570). The funnel-plot analysis showed asymmetrical shape for severe cases (Figure 6), indicating publication bias; Egger’s test indicated significant small-study effects for severe cases (p = 0.027).Figure 5
Funnel plot for mortality.Figure 6
Funnel plot for severe cases.


## 3.6. Sensitivity Analysis

Sensitivity analysis for between-study heterogeneity and analytical methods was performed to show the robustness of the finding. The analysis showed that the result was stable except for the exclusion of three studies [18, 21, 33] that changed the conclusion (Figure 7).Figure 7
Sensitivity analysis: forest plot for mortality of COVID-19 patients taking steroids versus nonsteroids.The rationale for the use of corticosteroids is to decrease the host inflammatory responses in the lungs, which may lead to acute lung injury and acute respiratory distress syndrome [6]. Because of the high amount of cytokines induced by COVID-19 infection, corticosteroids were used frequently for the treatment of patients with severe illness, for possible benefit by reducing inflammatory-induced lung injury [24]. There were potential harms and a lack of proven benefit for corticosteroid cautions against their routine use in patients with COVID-19 [6].Our analysis demonstrated that the mortality rate was comparable in COVID-19 patients treated with corticosteroids versus noncorticosteroids. However, in patients with critically ill COVID-19 patients, even though nonsignificant (RR = 0.89; 95% CI: 0.62–1.27;p = 0.52), a lower mortality rate in corticosteroid treatment groups was observed. Evidence suggests that cytokine storm, a hyperinflammatory state resembling secondary hemophagocytic lymphohistiocytosis (HLH), is a contributing factor in COVID-19-associated mortality [49].In our finding, there were no significant differences in mortality between the corticosteroid and noncorticosteroid treatment groups in critically ill COVID-19 patients. The initial clinical trial results from the United Kingdom (UK) showed that dexamethasone, a corticosteroid, can be lifesaving for patients who are critically ill with COVID-19. For patients on ventilators, the treatment was shown to reduce mortality by about one-third, and for patients requiring only oxygen, mortality was cut by about one-fifth, according to preliminary findings shared with the World Health Organization (WHO) [50].The most commonly invoked rationale for giving steroids in patients with severe COVID-19 is to modulate the destructive inflammatory immune response that occurs with advancing disease. The guidelines recommend against using corticosteroids to try to modulate the immune system in mechanically ventilated COVID-19 patients without acute respiratory distress syndrome (ARDS) but do recommend steroids in those with COVID-19 and ARDS [51]. Our finding demonstrates that there is an association between severe COVID-19 and corticosteroid therapy (RR = 1.10; 95% CI, 1.03–1.19, p = 0.007).A previous meta-analysis in persons with SARS-CoV-2, SARS-CoV, or MERS-CoV (Middle East respiratory syndrome coronavirus) infection indicated that corticosteroid did not significantly reduce the risk of death [52]. Another meta-analysis that included 5 studies indicated a lack of benefit of corticosteroid therapy on mortality in critically ill patients with COVID-19 [53]. In addition, a review that included 15 studies with coronavirus-infected patients (2 studies with COVID-19 patients) showed that corticosteroid treatment was associated with higher mortality and critical patients were more likely to require corticosteroids therapy [54].Some of the limitations of this meta-analysis are as follows: the included studies are retrospective cohort studies, there is a high degree of between-study heterogeneity, and mortality may be influenced by other therapeutic options.


## 4. Conclusion

No significant differences in mortality between the corticosteroid and noncorticosteroid treatment groups were observed. There was no significant reduction in mortality in critically ill COVID-19 patients treated with corticosteroids. More randomized clinical trials are needed to further verify this conclusion.



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