Comparison of Associations Between Glucocorticoids Treatment and Mortality in COVID-19 Patients and SARS Patients: A Systematic Review and Meta-Analysis : Shock

Secondary Logo

Journal Logo

Advanced Search
Clinical Science Aspects

Comparison of Associations Between Glucocorticoids Treatment and Mortality in COVID-19 Patients and SARS Patients: A Systematic Review and Meta-Analysis

Li, Jianbo∗; Liao, Xuelian∗; Zhou, Yue∗; Wang, Luping∗; Yang, Hang∗; Zhang, Wei†; Zhang, Zhongwei∗; Kang, Yan∗

Author Information

∗Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China

†Molecular Medicine Research Center, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China

Address reprint requests to Yan Kang, Department of Critical Care Medicine, West China Hospital, Sichuan University, 37 Guo Xue Xiang Street, Chengdu, Sichuan 610041, China. E-mail: [email protected]; Co-correspondence: Zhongwei Zhang, Department of Critical Care Medicine, West China Hospital, Sichuan University, 37 Guo Xue Xiang Street, Chengdu, Sichuan 610041, China. E-mail: [email protected].

Received 11 December, 2020

Revised 24 December, 2020

Accepted 17 January, 2021

The protocol for this review and meta-analysis was registered with PROSPERO (CRD42020193823).

Additional data available from the corresponding author on reasonable request at [email protected].

This work is supported by the Project of Novel Coronavirus Pneumonia in West China Hospital (HX2019nCoV027). The study's funders had no role in the design and conduct of the study, data collection, data analysis, data interpretation, or writing of the report.

JL, ZZ, and YK conceived the study and designed the protocol. JL and XL performed the literature search. HY, WZ, YZ, and LW selected the studies, exacted the relevant information, and assessed the risk of bias of included studies. JL synthesized the data and wrote the first draft of the paper. All authors contributed to critically revising successive drafts and approved the final version. JL, ZZ, and YK are guarantors. The corresponding authors avouch that all listed authors meet authorship criteria and that no other qualified authors have been omitted.

The authors report no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal's Web site (www.shockjournal.com).

SHOCK 56(2):p 215-228, August 2021. | DOI: 10.1097/SHK.0000000000001738

Abstract

INTRODUCTION

The coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS) are both coronavirus-caused pandemics that broke out in 2019 and 2003, respectively. The SARS epidemic has passed, but COVID-19 is ravaging the world. As of early November 2020, nearly 50 million people have been confirmed with COVID-19, and 1.2 million died because of COVID-19 (1).

Glucocorticoids, one of the non-specific immunosuppressants, were the mainstay of immunotherapy during the SARS epidemic, but its role has been a lasting controversy, same in the COVID-19 epidemic. Till July 2020, RECOVERY trial, a large clinical randomized controlled trial (RCT) from the UK, involving 6,425 patients, reported an absolute decrease in all-cause mortality of 2.8% in COVID-19 patients receiving a low dose of dexamethasone compared with those receiving usual care (2). Lately, a prospective meta-analysis involved seven RCTs concluded systemic glucocorticoids were associated with decreased all-cause mortality in critically ill patients with COVID-19 (3). However, scholars pointed out that removing the RECOVERY trial, the result of that meta-analysis changed to no statistical significance (4). Therefore, to obtain a robust product, more ongoing RCTs should be included.

Although evidence has shown severe dysregulated host inflammatory and immunity response is deadly in both COVID-19 and SARS patients (5–8), their epidemiology and clinical manifestations are substantial differences due to the subtle differences in pathogenesis (9, 10). We assume that the response to glucocorticoids treatment is different between the two diseases. Moreover, which doses, timing, and types of glucocorticoids treatment are more effective, and whether there are any other survival benefit subgroups besides critically ill patients have not been determined. Therefore, we conducted this systematic review and meta-analysis to provide more clues in these undetermined aspects.

METHODS

Guidance and protocol

We followed the standards developed by the meta-analysis of observational studies in epidemiology (MOOSE) (11) and preferred reporting items for systematic reviews and meta-analyses (PRISMA) (12) for reporting our study. The protocol for this review and meta-analysis was registered with PROSPERO (CRD42020193823).

Eligibility criteria

We considered studies to be eligible if they met the following PICOS criteria (participants, interventions, comparators, outcomes, and study design). The participants of interest included patients (adults/children) who were diagnosed with COVID-19 or SARS. The intervention included any type of glucocorticoids, including but not limited to hydrocortisone, prednisolone, methylprednisolone, prednisone, dexamethasone, and triamcinolone, compared with placebo or usual care (which may have included antiviral, antibiotic and antifungal therapy, intravenous immunoglobulin, or respiratory support, if needed). The primary outcome was all-cause mortality (including 28- or more-day mortality, 14–28-day mortality, and 7-day mortality). All-cause mortality rates were used to compute the pooled analysis on 7-day mortality if actual 7-day mortality rates failed to be neither extracted from the published studies nor obtained from study authors. The secondary outcome was the mortality-including composite outcome, including death and mechanical ventilation or intensive care unit (ICU) admission. The definitions of outcomes are presented in Supplementary Table 1, https://links.lww.com/SHK/B217. Both RCTs and observational studies (including cohort studies, case-control studies, case series) were included.

Studies were excluded if they were before-after studies, case series with no more than 10 patients, overlapping/repeated cohort data, and no or contaminated control design.

Literature search

Two of the authors (JL and XL) developed and executed the search strategy of several databases: Medline (Ovid), Embase (Ovid), EBSCO (H.W. Wilson: OmniFile Full-Text Mega), ScienceDirect, Web of Science (All database), Cochrane Library, from 2002 to October 7, 2020. We also searched ClinicalTrials.gov and consulted the WHO International Clinical Trials Registry Platform to identify any ongoing or unpublished eligible studies. To maximize the search for relevant articles, we reviewed reference lists of identified studies, systematic reviews, and review articles on the same topic. We did not apply language or publication status restrictions. Supplementary Table 2, https://links.lww.com/SHK/B218 presents the details of the search strategy.

Study selection

After removing duplicates, two independent groups of four authors (HY and WZ; YZ and LW) screened the titles and abstracts to determine whether the citation met the participants and intervention eligibility criteria. They obtained full texts and then further screed when studies met all the rest eligibility criteria. Disagreements between groups were resolved by consensus, and if necessary, consultation with a third author (ZZ).

Data collection process

Two independent groups of four authors (HY and WZ; YZ and LW) extracted data from included studies into standard data collection forms and created tables for quality assessment evidence and information. Evidence of severity of illness and administration of glucocorticoids reported in the eligible studies were collected and categorized according to the predefined (Supplementary Table 1, https://links.lww.com/SHK/B217).

Assessment of risk of bias

Two independent groups of four authors (HY and WZ; YZ and LW) performed the risk of assessment using the Revised Cochrane risk-of-bias tool for randomized trials and using the Newcastle-Ottawa-Scale (NOS) (13) for observational studies. The included randomized trials were assessed for randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, selection of the reported result. Each domain was assessed as low risk, some concerns, or a high risk of bias. The study's overall risk of bias was determined by the highest risk of bias for any criteria. The included observational studies were assessed for selection, comparability, exposure for case-control or outcome for cohort studies. Each domain is composed of two to four items of criteria, and each criterion was scored in the form of stars. A total score of 8 or 9 was assessed as low risk of bias, 6 or 7 as some concerns, and ≤5 as high risk. Disagreements between groups were resolved by consensus, and if necessary, consultation with a third author (ZZ).

Data synthesis

We performed statistical analyses that used the meta package in R (version 4.0.1; The R Project for Statistical Computing). Analyses were conducted for the intention-to-treat-based outcomes reported from RCTs and conducted for the narrowest-95%-confidence-interval-based data of risk for outcomes reported from observational studies. We equivalently transformed hazard ratios (HRs) (14) and odds ratios (ORs) (15) into risk ratios (RRs) and log-transform these effect sizes as well as their standard errors first before they were pooled. We used RRs and their associated 95% confidence interval (CI) to assess outcomes, as well as a prediction interval (PI) for the effect of future studies based on present (16), and we considered a two-tailed P value of less than 0.05 to be statistically significant. We examined heterogeneity using the I2 test. If non-significant heterogeneity was present (I2 < 50%), we used both fixed-effects and random-effects models to pool outcomes; we used random-effects models when significant heterogeneity was present (I2 ≥50%).

The possibility of publication bias was qualitatively visualized through contour-enhanced funnel plots and quantitatively tested through the Egger test. Duval and Tweedie's trim-and-fill procedure was also adopted to estimate the actual effect size when the “missing” small studies had been published (17).

Trial sequential analysis

We performed a trial sequential analysis to explore whether RCTs’ cumulative data were adequately powered to evaluate outcomes. Trial sequential analysis (18) (a Java-based software application, version 0.9.5.10) was used to calculate the required information size, and the O’Brien-Fleming approach was adopted to compute trial sequential monitoring boundaries. An optimal information size was calculated based on the event proportion of outcomes in the control arm, two-sided 5% risk of type I error, 20% risk of type II error (power 80%), and an anticipated relative risk reduction of more than 10% in this study.

Multimodel inference

We performed multimodel inference to examine which possible predictor combinations provide the best fit, and which predictors are the most important ones overall (19). The “dmetar” package in R was used to calculate the multimodel inference coefficients for each predictor and all predictors and obtain model-averaged importance of the predictors’ plot. A total of seven factors were considered input predictors: incidence of events in control, the severity of illness, doses of glucocorticoids, types of glucocorticoids, the timing of glucocorticoids, primary data type, and time frame of mortality. No prior knowledge was available on how these predictors are related to effect sizes in our meta-analysis.

Subgroup analysis

We planned several analyses to test interactions according to the following variables: age (elder [defined as ≤65 years plus or minus 5 year] and young [defined as > 65 years plus or minus 5 year]); sex (man and women); incidence of events in control (≤5%, 5%–10%, 10%–20%, 20%–40%, 40%–80%, and 80%–100%); severity of illness (mild or moderate, severe, critically severe, and severe or critically severe); acute respiratory distress syndrome (ARDS) (with and without); diabetes (with and without); doses (equivalent methylprednisolone) of glucocorticoids (low dose [< 90 mg/day or <1.5 mg/kg/day], medium-high dose [90 mg/day–250 mg/day or <1.5 mg/kg/day–4 mg/kg/day], and pulse [250 mg/day–500 mg/day]); types of glucocorticoids (dexamethasone, hydrocortisone, methylprednisolone, and multiple types); timing of glucocorticoids (non-early and early [defined as glucocorticoids therapy within the first 48 h of admission or within 10 days from illness onset to glucocorticoids therapy]); and laboratory biomarkers (the specific classification depends on the data provided by the included studies).

Sensitivity analyses

We conducted sensitivity analyses by excluding studies with high, some concerns, or both risks of bias; excluding the largest studies; excluding studies reporting multiple glucocorticoids use; excluding studies identified by clustering-algorithms-dependent Graphic Display of Heterogeneity (GOSH) plots (20–23); excluding studies reporting 7-day mortality; combining data from RCTs and observational; using odds ratios to assess outcomes.

RESULTS

Eligible studies and study characteristics

Of the 6,136 records, 81 studies (2, 24–103) involved a total of 45,935 patients who were included in the final meta-analysis (Fig. 1). Table 1 shows a summary of the included studies. The studies comprised 10 RCTs for COVID-19, including 7,898 patients, 59 observational studies for COVID-19 including 26,735 patients, and 12 observational studies for SARS including 11,302 patients. These studies for COVID-19 reported median mortality of 17% and a median age of 57.4 years among their included patients, and studies for SARS reported median mortality of 6.3% and a median age of 46 years among their included patients. Supplementary Table 3, https://links.lww.com/SHK/B219 gives details of those studies.

F1
Fig. 1:
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for the Article Selection Process.
Table 1 - Summary characteristics of included studies
Characteristics No of studies (no. of patients)
Eligible studies
 Total no. of studies (no. of patients) 81 (45,935)
 RCTs for COVID-19 10 (7,898)
 Observational studies for COVID-19 59 (26,735)
 Observational studies for SARS 12 (11,302)
Median (IQR) %, mortality
 COVID-19 17 (11.7–24)
 SARS 6.3 (4.6–12.6)
Median (IQR) %, male
 COVID-19 57.4 (50.2–64.6)
 SARS 46 (42.2–49.7)
Median (IQR), age (years)
 COVID-19 61 (55–66)
 SARS 37 (35–39)
Median (IQR) follow-up (days)
 COVID-19 28 (24–30)
 SARS 45 (28–90)
Country
COVID-19
 European 18 (15,750)
 American 6 (2,872)
 Asian-pacific 43 (15,105)
 Multinational 2 (910)
SARS
 Asian-pacific 11 (9,369)
 Multinational 1 (1,935)
Administration of glucocorticoids:
Types
COVID-19
 Dexamethasone 3 (2,298)
 Hydrocortisone 3 (474)
 Methylprednisolone 19 (1,612)
 Multiple types 9 (3,058)
 Not available 35 (5,031)
SARS
 Hydrocortisone 1 (621)
 Methylprednisolone 3 (746)
 Multiple types 3 (1,498)
 Not available 5 (1,493)
Median (IQR), doses (equivalent methylprednisolone, mg/day)
 COVID-19 61 (47–80)
 SARS 97 (80–120)
COVID-19 indicates coronavirus disease 2019; IQR, interquartile range; RCTs, randomized controlled trials; SARS, severe acute respiratory syndrome.

Supplementary Figures 1, https://links.lww.com/SHK/B220 and 2, https://links.lww.com/SHK/B221 show a risk bias for RCTs. Seven trials had a low risk of bias, and three trials had a risk of some concerns. Supplementary Tables 4, https://links.lww.com/SHK/B222 and 5, https://links.lww.com/SHK/B223 show risk bias for observational studies. Of these studies, one study reported outcome data with low risk, 15 studies with low risk or risk of some concerns, 16 studies with risk of some concerns, six studies with high risk or risk of some concerns, and 33 studies with high risk.

Primary outcome: all-cause mortality

All 10 RCTs reported all-cause mortality for COVID-19. The overall RR (0.88; 95% CI, 0.82–0.94; I2 = 26%; PI, 0.81–0.95) (Fig. 2) revealed an association between glucocorticoids treatment and improved all-cause mortality in COVID-19 patients. There was no statistically significant difference in that association between 7-day, 14- to 28-day, and 28- or more-day mortality. The trial sequential analysis confirmed that the overall required information size was met for all-cause mortality (Supplementary Figure 3, https://links.lww.com/SHK/B224). Similar results were observed for all-cause mortality in all conducted sensitivity analyses (Supplementary Table 6, https://links.lww.com/SHK/B225 and Supplementary Figure 26, https://links.lww.com/SHK/B226). Funnel plot analysis showed no asymmetry (Supplementary Figure 12, https://links.lww.com/SHK/B227), and the Egger test (P = 0.747) detected no significant small-study effects. A total of 52 observational studies for COVID-19 reported all-cause mortality, and the pooled RR from studies of all risk levels showed an association between glucocorticoids treatment and increased all-cause mortality in COVID-19 patients (RR, 1.32; 95% CI, 1.08–1.61; I2 = 99%) (Supplementary Figure 5, https://links.lww.com/SHK/B228), while result from 11 studies with low risk of bias was similar to that from RCTs (RR, 0.68; 95% CI, 0.5–0.94; I2 = 67%) (Supplementary Table 6, https://links.lww.com/SHK/B225). Funnel plot analysis showed no asymmetry among observational studies reporting all-cause mortality for COVID-19 (Supplementary Figure 14, https://links.lww.com/SHK/B229).

F2
Fig. 2:
Forest plot of RCTs for COVID-19 and observational studies with low risk of bias for SARS. COVID-19 indicates coronavirus disease 2019; RCT, randomized controlled trial; SARS, severe acute respiratory syndrome.

A total of 10 observational studies for SARS reported all-cause mortality. Results from studies with low risk of bias revealed a statistically significant association between glucocorticoids treatment and improved all-cause mortality in SARS patients (RR, 0.48; 95% CI, 0.29–0.79; I2 = 10%; PI, 0.21–1.09) (Fig. 2). Though the overall RR from studies of all risk levels showed no association between glucocorticoids treatment and all-cause mortality in SARS patients (RR, 1.1; 95% CI, 0.74–1.63; I2 = 99%) (Supplementary Figure 7, https://links.lww.com/SHK/B230), sensitivity analyses excluding studies with a high risk of bias or excluding studies reporting use of multiple glucocorticoids showed a similar result with that from studies with low risk of bias (RR, 0.67; 95% CI, 0.45–1; I2 = 97%) (Supplementary Table 6, https://links.lww.com/SHK/B225)). Funnel plot analysis showed no asymmetry (Supplementary Figure 16, https://links.lww.com/SHK/B231), and the Egger test (P = 0.489) detected no significant small-study effects, and additionally results from the Duval and Tweedie's trim-and-fill procedure (with five added studies) were identified with our initial results.

Secondary outcome: mortality-including composite outcome

Evidence from RCTs showed glucocorticoids treatment was associated with significant reduction in all-cause mortality-including composite outcome of COVID-19 (RR, 0.89; 95% CI, 0.82–0.98; I2 = 0%; PI, 0.69–1.15) (Fig. 2), especially significant reduction in 28- or more-day mortality-including composite outcome (RR, 0.9; 95% CI, 0.81–1; I2 = 40%) (Fig. 2). In the trial sequential analysis, the cumulative z-curve nearly reached the monitoring boundary, but the number of involved patients failed to meet the required information size of 9,347. Sensitivity analyses showed no significantly different results (Supplementary Table 6, https://links.lww.com/SHK/B225). Funnel plot analysis showed no significant asymmetry (Supplementary Figure 13, https://links.lww.com/SHK/B232), the Egger test (P = 0.403) detected no significant small-study effects. Additionally, Duval and Tweedie's trim-and-fill procedure (with two added studies) showed similar results with the initial ones.

Evidence from observational studies of all risk levels showed no significant association between glucocorticoids treatment and all-cause mortality; however, evidence indicated a significant reduction in 28- or more-day mortality-including composite outcome in COVID-19 patients receiving glucocorticoids treatment (RR, 0.53; 95% CI, 0.43–0.66; I2 = 83%) (Supplementary Figure 6, https://links.lww.com/SHK/B233). Sensitivity analyses excluding studies with a high risk of bias confirmed the significant reduction both in 28- or more-day and all-cause mortality-including composite outcome (Supplementary Table 6, https://links.lww.com/SHK/B225). No significant small-study effects were observed among these observational studies reporting the mortality-including composite outcome of COVID-19 (Supplementary Figure 15, https://links.lww.com/SHK/B234). Only one observational study reported conflicting data of mortality-including composite outcomes of SARS and pooled RR showed no significant association between glucocorticoids treatment and all-cause mortality in SARS patients (RR, 0.84; 95% CI, 0.17–4.3; I2 = 96%) (Supplementary Figure 8, https://links.lww.com/SHK/B235).

Multimodel inference and subgroup analysis

Multimodel inference found that incidence of events in control, doses of glucocorticoids, and types of glucocorticoids were the top three important predictors for all-cause mortality in COVID-19 patients (Supplementary Figure 9, https://links.lww.com/SHK/B236). The former two were also the most important predictors for the mortality-including composite outcome of COVID-19 (Supplementary Figure 10, https://links.lww.com/SHK/B237). Differently, the types of glucocorticoids became the only most important predictor for all-cause mortality in SARS patients (Supplementary Figure 11, https://links.lww.com/SHK/B238).

Subgroup analysis revealed that all-cause mortality was significantly lower in COVID-19 patients with characters of being accompanied by ARDS, taking low-dose or pulse glucocorticoids, being severe or critically severe, being man, and taking dexamethasone or methylprednisolone (Fig. 3). Similar results occurred when the mortality-including composite outcome was considered (Fig. 4). Some differently, all-cause mortality was significantly lower in SARS patients with characters of taking medium-high dose glucocorticoids, being severe or critically severe, early taking glucocorticoids, and taking methylprednisolone or prednisolone (Fig. 5). Because two of three studies for mild or moderate SARS patients reported zero events in both arms, there was no enough power to draw a convincing conclusion in these subgroup patients. Moreover, early taking glucocorticoids seemed to have no significant association with improved mortality in COVID-19 patients until when mechanical ventilation or ICU admission outcome was additionally considered (Figs. 4 and 5).

F3
Fig. 3:
Subgroup analysis of association between mortality and glucocorticoids for COVID-19 by clinical characteristics. COVID-19 indicates coronavirus disease 2019.
F4
Fig. 4:
Subgroup analysis of association between composite outcome and glucocorticoids for COVID-19 by clinical characteristics.
F5
Fig. 5:
Subgroup analysis of association between mortality and glucocorticoids for SARS by clinical characteristics.

Importantly, pooled effects for COVID-19 and SRAS patients’ outcomes strongly correlated to the incidence of events in control. The benefit was only seen among studies that reported more than 20% of the incidence of events in control but was not seen for the incidence of less than 20% (Figs. 3–5). Pooled effects even showed a significant association between glucocorticoids treatment and worsen mortality reported from studies with the incidence of events in control from 0% to 5% (Figs. 3 and 5). We stratified studies according to these incidences to avoid the potential bias caused by the difference of outcome incidence reported in control (Supplementary Figure 17-24, https://links.lww.com/SHK/B239, https://links.lww.com/SHK/B240, https://links.lww.com/SHK/B241, https://links.lww.com/SHK/B242, https://links.lww.com/SHK/B243, https://links.lww.com/SHK/B244, https://links.lww.com/SHK/B245, https://links.lww.com/SHK/B246). Interestingly, results implied that COVID-19 patients who were critically severe (including severe ARDS) but not only severe (including mild ARDS), and COVID-19 patients who of critical severity were old but not young, or men but not women were more likely to obtain survival benefit from glucocorticoids treatment (Supplementary Figure 17-23, 25, https://links.lww.com/SHK/B239, https://links.lww.com/SHK/B240, https://links.lww.com/SHK/B241, https://links.lww.com/SHK/B242, https://links.lww.com/SHK/B243, https://links.lww.com/SHK/B244, https://links.lww.com/SHK/B245, https://links.lww.com/SHK/B247).

We also investigated the reported biomarkers that can predict the efficacy of glucocorticoids for COVID-19 patients though the data was limited (Fig. 6). These potential biomarkers included C-reactive protein (CRP), D-dimer, lactate dehydrogenase (LDH), lymphocytes, brain natriuretic peptide (BNP), cardiac troponin I (cTnI), and cardiac troponin T (cTnT). The results indicated that COVID-19 patients with CRP ≥100 mg/L, LDH <492 U/L, or lymphocytes <1.2 × 109/L had a lower risk of death when receiving glucocorticoids treatment. Moreover, patients with BNP >100 ng/L seemed to experience a lower risk of the mortality-including composite outcome. However, when CRP <100 mg/L, glucocorticoids treatment, on the contrary, would cause a higher risk of the mortality-including composite outcome.

F6
Fig. 6:
Subgroup analysis of association between outcomes and glucocorticoids for COVID-19 by laboratory biomarkers.

Complications of glucocorticoids

We finally analyzed short-term complications of glucocorticoids for COVID-19 and SARS. For severe or critically severe ill COVID-19 patients, glucocorticoids treatment would not increase the incidences of hyperglycemia or nosocomial infections, or delay viral clearance; however, for mild or moderate ill patients, the risk of the above complications was increased (Supplementary Figure 27, https://links.lww.com/SHK/B248). For overall SARS patients, glucocorticoids treatment increased the risks of hyperglycemia and nosocomial infections (Supplementary Figure 28, https://links.lww.com/SHK/B249). Because of the limited data, we failed to investigate the differences between severities regarding complications among SARS patients.

DISCUSSION

In this meta-analysis of 10 RCTs (including 7,898 COVID-19 patients) and 71 observational studies (including 26,735 COVID-19 patients and 11,302 SARS patients), glucocorticoids treatment was significantly associated with reduced all-cause mortality and mortality-including composite outcome in both COVID-19 and SARS patients. Subgroup analyses demonstrated that among COVID-19 patients, the beneficial effect in our outcomes was associated with being accompanied by severe ARDS but not mild ARDS, taking low-dose or pulse glucocorticoids, being critically severe but not only severe, being of critical severity, and old but not young, being of critical severity and men but not women, non-early taking glucocorticoids, taking dexamethasone or methylprednisolone, and with the increased inflammatory state; among SARS patients, that beneficial effect was associated with taking medium-high dose glucocorticoids, being severe or critically severe, early taking glucocorticoids, and taking methylprednisolone or prednisolone. Our findings suggested glucocorticoids treatment's survival benefits both in COVID-19 and SARS patients and its association with the severity of illness; however, there were differences in the other aspects, mainly regarding sex- and age-specific effects, doses, and timing of glucocorticoids treatment.

Principal findings and comparison with other studies

As of writing this manuscript (early November 2020), 16 meta-analyses (104–119) have examined the use of glucocorticoids in patients with COVID-19 or coronavirus infections. Regarding mortality, four meta-analyses (106, 107, 112, 113, 118) included RCTs (one including seven RCTs, three including one or two RCTs) and the rest only included observational studies. Of these meta-analyses, five (104–108) found that glucocorticoids treatment decreased all-cause mortality, seven (109–115) found no association between glucocorticoids treatment and all-cause mortality, and the others (116–119) found glucocorticoids treatment increased all-cause mortality. In general, meta-analyses that supported glucocorticoids treatment mostly identified studies on COVID-19 patients who were severely-ill suffered from ARDS. The latest meta-analysis (107) was a prospective meta-analysis involving seven clinical trials of 1,703 critically ill patients with COVID-19. Findings in this meta-analysis showed that administration of systemic glucocorticoids was associated with lower 28-day all-cause mortality (OR based on a fixed-effect meta-analysis, 0.66; 95% CI, 0.53–0.82; I2 = 15.6%). Results of this prospective meta-analysis without considering other ongoing trials were limited owing to its risk of selective reporting or publication bias. Moreover, the RECOVERY trial (2) exerted the most influence (comprising 59% patients and contributing 57% of the weight) in that meta-analysis, and if the RECOVERY trial was excluded, results changed to no statistical significance (4). Before that study, a single-arm meta-analysis (105) investigated the mortality in COVID-19 patients who were accompanied with ARDS and received glucocorticoids treatment and found that compared with 39% of all-cause mortality among COVID-19 patients with ARDS, glucocorticoids treatment decreased all-cause mortality to 28%. However, the limitation of the single-arm meta-analysis was obvious due to its non-pairwise design. There was one meta-analysis (119) investigating glucocorticoids use on mortality in SARS patients alone. The meta-analysis found no association between glucocorticoids treatment and all-cause mortality in SARS patients (RR, 2.56; 95% CI, 0.99–6.63; I2 = 77.4%). However, results from that meta-analysis were restricted owing to inconsistency (significant heterogeneity across involved studies), published bias (only seven studies), and risk of bias (including observational studies of all risk levels).

The findings of our meta-analysis of the association of glucocorticoids administration with improved all-cause mortality were in line with the recently published results on COVID-19. We further confirmed these findings by including additional three RCTs (32, 85, 93) and conducting the sensitivity analysis by excluding the largest trial (RECOVERY trial). Of the three additional RCTs including 546 patients, two trials (85, 93) involved patients of mild or moderate ill and one trial (93) reported 14-day mortality and composite outcome, which provided more information than the previously conducted meta-analysis of only critical patients. Moreover, the additional RCTs improved the power of the trial sequential analysis and its results reinforced our findings. Besides, we also investigated the effect of glucocorticoids treatment on the mortality-including composite outcome. We found a protective role of glucocorticoids treatment in 28- or more-day mortality-including composite outcomes in COVID-19 patients. Furthermore, results from observational studies with a low risk of bias were like those from RCTs.

Our findings of the survival benefit of glucocorticoids treatment in SARS patients differ from previously published results on SARS. This difference could be explained by identifying more eligible studies and stratifying included studies according to the risk of bias in our meta-analysis. The high risk of bias mainly came from studies reporting multiple glucocorticoids use, which was also confirmed by multimodel inference. After removing these studies of a high risk of bias, survival benefit from glucocorticoids treatment was evident.

Another important difference in our meta-analysis is that we systematically compared the differences in the effects of glucocorticoids treatment on mortality between COVID-19 and SARS patients across subgroups defined by patient characteristics before receiving glucocorticoids treatment, by disease severity, and by details of glucocorticoids regimen. We assessed optimal doses, types and timing of treatment, and other potential benefit subgroups by separately showing evidence across different levels of risk of bias from RCTs and observational studies. Results indicated that the old or men being critically severe or with severe ARDS were more likely to obtain survival benefit from glucocorticoids treatment among COVID-19 patients; however, there was no evidence to support sex- or age-specific effect in SARS patients. Moreover, medium- or long-term types of glucocorticoids were associated with improved mortality both in COVID-19 and SARS patients. Regarding doses, COVID-19 patients were likely to benefit from low-dose or pulse glucocorticoids treatment; however, SARS patients may be more likely to benefit from medium-high dose glucocorticoids treatment. As for treatment timing, benefits likely preferred to early taking glucocorticoids in SARS patients; however, no strong evidence supported early taking glucocorticoids in COVID-19 patients. In brief, optimal glucocorticoids regimens were different between COVID-19 and SARS patients, especially regarding sex- and age-specific effects, doses, and treatment timing. These differences are likely due to the different immunological pathways between COVID-19 and SARS. SARS-CoV-2 that causes COVID-19 seems weakness in aggression in the early stage of infection when compared with SARS-CoV-1 that causes SARS. SARS-CoV-2 is more like a cunning “gentle killer”—it infects and hijacks host cells but does not lyse cells, then blocks interferons signaling of cells, by which it delays immune response (8). Thus, moderate inflammation occurs or abruptly deteriorates in the late stage of COVID-19, which needs late immunosuppressant of low dose or pulse; however, moderate-high inflammation occurs early and may persist for quite a while in SARS patients, which needs early immunosuppressant of medium-high dose. The aged with innate immune of deficiency allows SARS-CoV-2 to lurk and duplicate itself at alveoli for a long time and easily triggered cell-mediated immune response in the late stage of infection, which leads an outbreak of uncontrollable inflammatory cascade and caused ARDS (120). Thus, our results indicated patients with the increased inflammatory state would benefit more from glucocorticoids treatment. Besides, sex hormones could influence immune response or disease severity and were associated with female protection against SARS-CoV-2 (121). A recent computational study revealed the mechanism by which quinone derivatives could inhibit the SARS-CoV-2 Mpro protease (122). Methylprednisolone and dexamethasone are both methide quinones; however, clinical evidence showed dexamethasone was more effective in improving outcomes in COVID-19 patients compared to methylprednisolone (123). The underlying rationale needs to be further investigated; however, we failed to directly compare the effect of dexamethasone and methylprednisolone on COVID-19 or SARS due to lack of data.

Strengths and limitations

This systematic review and meta-analysis have several methodological strengths. We followed the recommendations of the MOOSE statement and PRISMA statement, including a priori protocol. This meta-analysis of all-cause mortality on COVID-19 met the optimum size in trial sequential analysis and was robust despite sensitivity analyses. We collected evidence from RCTs and observational studies, provided prediction intervals, and explored other predictors or confounding factors for all-cause mortality by multimodel inference. Through the systematic comparison of COVID-19 and SARS, we assessed potential benefit subgroups and the optimal regimens of glucocorticoids treatment. Considering potential bias caused by the various outcome incidence in control reported by studies, systematic subgroup analyses were also conducted across different outcome incidence levels in control.

Our study has limitations. First, the results of this meta-analysis on SARS were all from observational studies. Clinical heterogeneity is inevitable in these studies, including doses, types, timing, and therapy duration. Regarding statistical heterogeneity, the results of studies on SARS included in our analysis were variable, with a high degree of detected heterogeneity for the primary outcome of all-cause mortality (I2 = 98%), justifying by use of random-effects models when pooling data of all levels of risk of bias. By only the inclusion of studies with a low risk of bias, heterogeneity could be resolved but with a significant change in the primary outcome. Most studies with a high risk of bias reported multiple glucocorticoids use, which was the most important contributor to heterogeneity in the meta-analysis on SARS. There was a little heterogeneity (I2 = 26%) when pooling data of RCTs on COVID-19. This heterogeneity came from only one trial (32), which reported pulse use of glucocorticoids. GOSH plots identified this trial, and by the exclusion of this trial, heterogeneity could be eliminated without significant change in the primary outcome.

Second, though funnel plots showed no asymmetry no matter among RCTs or observational studies, no matter for primary or secondary outcomes, publication bias may exist when subgroup analyses were conducted. Some subgroup analyses failed to be conducted due to limited data. To ensure the quality of results, we analyzed RCTs and observational studies separately; however, this may increase publication bias in subgroup analyses.

Third, prevalent time from 16 years, treatments and diagnostic techniques for virus pneumonia have evolved. Therefore, the medical and technical background should be considered when comparing treatment effects on SARS and COVID-19. For example, the severity of illness or clinical classification differed between SARS and COVID-19. For SARS, there was no strict distinction between severe and critically severe, which brings us difficulty in interpreting related results.

Implications for practice

For many years and even today, glucocorticoids have aroused much controversy in treating viral pneumonia, including H1N1, SARS, MERS, and COVID-19. Historically, there was almost no hard evidence to support glucocorticoids treatment in this pneumonia. Even reviews and meta-analyses of this treatment indicated increased mortality, delayed viral clearance, and increased risk of superinfection (124, 125). Therefore, WHO suggests glucocorticoids use only under special circumstances, i.e., septic shock or bronchoconstriction, however, based heavily on empirical evidence. Until the completion of the RECOVERY trial of COVID-19 therapy, the largest relevant RCT announced at present, from which evidence supported glucocorticoids treatment in critically ill COVID-19 patients who were on mechanical ventilation or oxygen support, we’re looking at glucocorticoids therapy again. Though at present much evidence supports its use in critically ill COVID-19 patients, we cannot blindly extend it to other subgroups of COVID-19 or other viral pneumonia. Our meta-analysis further revealed the massive impact of severity of illness on the role of glucocorticoids. It confirmed its efficacy in reducing mortality and the mortality-including composite outcome for COVID-19 patients being critically severe or with severe ARDS but not those being only severe or with mild ARDS. By comparing COVID-19 and SARS, we found differences between these diseases and further determined the optimal treatment regimens regarding sex- and age-specific effects, doses, and treatment timing. These findings appear to indicate that glucocorticoids should be prescribed at a low dose or pulse use but not at early taking (within 10 days from illness onset to glucocorticoids therapy) for COVID-19 patients; however, this situation is complementary to that of SARS. Furthermore, sex- or age-specific effect in COVID-19 patients should be noted when considering this treatment. Old age or male gender was usually related to severe illness and results may be affected by confounding effects of disease severity. However, when stratified according to severity, sex- or age-specific effects still existed across different severity levels. Thus, we infer that sex and age may be severity-of-illness-independent factors for the risk of death. The further trials or clinical therapy regimens should seriously consider the sex, age, and timing (severity-of-illness) when administrating glucocorticoids. Besides, increased inflammatory markers should be also considered, because most of them are related to the severity-of-illness. We believe our findings would bring light to the current clinical practice in glucocorticoids treatment of COVID-19.

CONCLUSIONS

The findings suggest that glucocorticoids treatment reduced all-cause mortality and mortality-including composite outcome both in COVID-19 and SARS patients of critical severity. However, further benefit subgroups for COVID-19, compared with SARS, should be those who were critical but not only severe, with severe ARDS but not mild ARDS, of critical severity and man but not women, of critical severity and old but not young, taking low-dose or pulse but not medium-high dose, non-early but not early taking, and with the increased inflammatory state. For SARS, lower mortality was observed among those who were taking medium-high dose glucocorticoids, being severe or critically severe, early taking glucocorticoids, and taking methylprednisolone or prednisolone. Suppl Figure 4 - https://links.lww.com/SHK/B250. Suppl Table 7 - https://links.lww.com/SHK/B251.

Acknowledgment

The authors thank Longhao Zhang (Chinese Evidence-based Medicine Centre, West China Hospital, Sichuan University) for his support in methodological suggestions for this meta-analysis.

REFERENCES

1. WHO: WHO Coronavirus Disease (COVID-19) Dashboard. Available at: https://covid19.who.int/ (accessed November 7, 2020).
2. Horby P, Lim WS, Emberson JR, Mafham M, Bell JL, Linsell L, Staplin N, Brightling C, Ustianowski A, Elmahi E, et al. Dexamethasone in hospitalized patients with Covid-19—preliminary report. N Engl J Med 2020; Online ahead of print.
3. WHO Rapid Evidence Appraisal for COVID-19 Therapies Working Group. Association between administration of systemic corticosteroids and mortality among critically ill patients with COVID-19: a meta-analysis. JAMA 324:1330–1341, 2020.
4. Tang HJ, Lai CC. The association between corticosteroid uses and mortality among severe COVID-19 patients. J Infect 82 (2):e24, 2021.
5. Zhand S, Saghaeian Jazi M, Mohammadi S, Tarighati Rasekhi R, Rostamian G, Kalani MR, Rostamian A, George J, Douglas MW. COVID-19: the immune responses and clinical therapy candidates. Int J Mol Sci 21 (15):5559, 2020.
6. Cameron MJ, Bermejo-Martin JF, Danesh A, Muller MP, Kelvin DJ. Human immunopathogenesis of severe acute respiratory syndrome (SARS). Virus Res 133 (1):13–19, 2008.
7. Channappanavar R, Perlman S. Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology. Semin Immunopathol 39 (5):529–539, 2017.
8. Vabret N, Britton GJ, Gruber C, Hegde S, Kim J, Kuksin M, Levantovsky R, Malle L, Moreira A, Park MD, et al. Immunology of COVID-19: current state of the science. Immunity 52 (6):910–941, 2020.
9. Hui DSC, Chan MCH, Wu AK, Ng PC. Severe acute respiratory syndrome (SARS): epidemiology and clinical features. Postgrad Med J 80 (945):373, 2004.
10. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395 (10223):497–506, 2020.
11. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA 283 (15):2008–2012, 2000.
12. Moher D, Liberati A, Tetzlaff J, Altman DG. PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339 (7716):b2535, 2009.
13. Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, Tugwell PThe newcastle-ottawa scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses. Available at: http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm (accessed April 3, 2020).
14. Spruance SL, Reid JE, Grace M, Samore M. Hazard ratio in clinical trials. Antimicrob Agents Chemother 48 (8):2787–2792, 2004.
15. Zhang J, Yu KF. What's the relative risk? a method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280 (19):1690–1691, 1998.
16. IntHout J, Ioannidis JPA, Rovers MM, Goeman JJ. Plea for routinely presenting prediction intervals in meta-analysis. BMJ Open 6 (7):e010247, 2016.
17. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 56 (2):455–463, 2000.
18. Brok J, Thorlund K, Gluud C, Wetterslev J. Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses. J Clin Epidemiol 61 (8):763–769, 2008.
19. Harrer M, Cuijpers P, Furukawa TA, Ebert DD, Doing meta-analysis in R: a hands-on guide. Available at: https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/ (accessed May 15, 2020).
20. Leisch F. FlexMix: a general framework for finite mixture models and latent class regression in R. J Stat Software 11 (8):1–18, 2004.
21. Olkin I, Dahabreh IJ, Trikalinos TA. GOSH: a graphical display of study heterogeneity. Res Synth Meth 3 (3):214–223, 2012.
22. Hartingan J, Wong M. Algorithm AS136: a K-means clustering algorithm. J Roy Stat Soc C Appl Stat 28 (1):100–108, 1979.
23. Schubert E, Sander J, Ester M, Kriegel HP, Xu XW. DBSCAN revisited: why and how you should (still) Uue DBSCAN. ACM Trans Database Syst 42 (3):19, 2017.
24. Wang Y, Jiang WW, He Q, Wang C, Wang BJ, Zhou P, Dong NG, Tong QX. A retrospective cohort study of methylprednisolone therapy in severe patients with COVID-19 pneumonia. Signal Transduct Target Ther 5 (1):57, 2020.
25. Wang R, Zhou XQ, Dong J, Wei R, Cao XT, Zhou YC, Wang J, Guo DH, Chen K, Zhou J, et al. Effects and adverse drug reactions of mtrisone in the treatment of patients with severe acute respiratory syndrome. Chin J Clin Pharmacol Therap 09:992–996, 2004.
26. Wang P, Li MY, Shi YL, Wang SX, Liu GF. Evaluating the effects of different treatments on severe acute respira tory syndrome. Shanxi Med J 2005; (04):270–272.
27. Scandinavian Critical Care Trials Group et al. Hydrocortisone for COVID-19 and severe hypoxia (COVID STEROID). Available at: https://ClinicalTrials.gov/show/NCT04244591 (accessed October 7, 2020).
28. Sanz-Herrero F, Puchades-Gimeno F, Ortega-Garcia P, Ferrer-Gomez C, Ocete-Mochon MD, Garcia-Deltoro M. Methylprednisolone added to tocilizumab reduces mortality in SARS-CoV-2 pneumonia: an observational study. J Intern Med 289:259–263, 2020.
29. Salton F, Confalonieri P, Santus P, Harari S, Scala R, Lanini S, Vertui V, Oggionni T, Caminati A, Patruno V, et al. Prolonged low-dose methylprednisolone in patients with severe COVID-19 pneumonia. medRxiv 7 (10):ofaa421, 2020.
30. Peking Union Medical College Hospital et al. Glucocorticoid therapy for COVID-19 critically ill patients with severe acute respiratory failure. Available at: https://ClinicalTrials.gov/show/NCT04244591 (accessed October 7, 2020).
31. Jia WD. Retrospective Study of the Effect of Glucocorticosteroids on the Treatment of Severe Acute Respiratory Syndrome. Sun Yat-sen Univ; 2006.
32. Edalatifard M, Akhtari M, Salehi M, Naderi Z, Jamshidi A, Mostafaei S, Najafizadeh SR, Farhadi E, Jalili N, Esfahani M, et al. Intravenous methylprednisolone pulse as a treatment for hospitalised severe COVID-19 patients: results from a randomised controlled clinical trial. Eur Respir J 56:2002808, 2020.
33. Dr. Negrin University Hospital et al. Efficacy of dexamethasone treatment for patients with ARDS caused by COVID-19 (DEXA-COVID19). Available at: https://ClinicalTrials.gov/show/NCT04325061 (accessed October 7, 2020).
34. Cruz AF, Ruiz-Antoran B, Gomez AM, Lopez AS, Sanchez PM, Soto GAC, Alonso SB, Garachana LJ, Gomez AG, Alijo AV, et al. A retrospective controlled cohort study of the impact of glucocorticoid treatment in SARS-CoV-2 infection mortality. Antimicrob Agents Chemother 64 (9):e01168–20, 2020.
35. Auyeung TW, Lee JS, Lai WK, Choi CH, Lee HK, Lee JS, Li PC, Lok KH, Ng YY, Wong WM, et al. The use of corticosteroid as treatment in SARS was associated with adverse outcomes: a retrospective cohort study. J Infect 51 (2):98–102, 2005.
36. Zhou F, Yu T, Du RH, Fan GH, Liu Y, Liu ZB, Xiang J, Wang YM, Song B, Gu XY, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 395 (10229):1054–1062, 2020.
37. Zha L, Li SR, Pan LL, Tefsen B, Li YS, French N, Chen L, Yang G, Villanueva EV. Corticosteroid treatment of patients with coronavirus disease 2019 (COVID-19). Med J Aust 212:416–420, 2020.
38. Yao QC, Wang P, Wang XG, Qie GQ, Meng M, Tong XW, Bai X, Ding M, Liu WM, Liu KK, et al. A retrospective study of risk factors for severe acute respiratory syndrome coronavirus 2 infections in hospitalized adult patients. Pol Arch Med Wewn 130 (5):390–399, 2020.
39. Yang XB, Yu Y, Xu JQ, Shu HQ, Xia JA, Liu H, Wu YR, Zhang L, Yu Z, Fang MH, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 8:475–481, 2020.
40. Yang KY, Sheng YH, Huang CL, Jin Y, Xiong N, Jiang K, Lu HD, Liu J, Yang JY, Dong YH, et al. Clinical characteristics, outcomes, and risk factors for mortality in patients with cancer and COVID-19 in Hubei, China: a multicentre, retrospective, cohort study. Lancet Oncol 21 (7):904–913, 2020.
41. Yan YL, Yang Y, Wang FW, Ren HH, Zhang SJ, Shi XL, Yu XF, Dong K. Clinical characteristics and outcomes of patients with severe covid-19 with diabetes. BMJ Open Diabetes Res Care 8 (1):e001343, 2020.
42. Yam LYC, Lau ACW, Lai FYL, Shung E, Chan J, Wong V. Corticosteroid treatment of severe acute respiratory syndrome in Hong Kong. J Infect 54 (1):28–39, 2007.
43. Xu JQ, Yang XB, Yang LY, Zou XJ, Wang YX, Wu YR, Zhou T, Yuan Y, Qi H, Fu SZ, et al. Clinical course and predictors of 60-day mortality in 239 critically ill patients with COVID-19: a multicenter retrospective study from Wuhan, China. Crit Care 24 (1):394, 2020.
44. Wu JF, Huang JQ, Zhu GC, Liu YH, Xiao H, Zhou Q, Si X, Yi H, Wang CP, Yang DY, et al. Systemic corticosteroids show no benefit in severe and critical COVID-19 patients in Wuhan, China: a retrospective cohort study. medRxiv 2020.
45. Wu CM, Chen XY, Cai YP, Xia JA, Zhou X, Xu S, Huang HP, Zhang L, Zhou X, Du CL, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med 180:934–943, 2020.
46. Writing Committee for the Remap- C. A. P. Investigators. Effect of hydrocortisone on mortality and organ support in patients with severe COVID-19: the REMAP-CAP COVID-19 corticosteroid domain randomized clinical trial. JAMA 324:1317–1329, 2020.
47. Wang ZL, Yang BH, Li QW, Wen L, Zhang RG. Clinical features of 69 cases with coronavirus disease 2019 in Wuhan, China. Clin Infect Dis 71 (15):769–777, 2020.
48. Wang ZH, Shu C, Ran X, Xie CH, Zhang L. Critically ill patients with coronavirus disease 2019 in a designated ICU: clinical features and predictors for mortality. Risk Manag Healthc Policy 13:833–845, 2020.
49. Wang K, Zhang ZG, Yu MY, Tao Y, Xie M. 15-day mortality and associated risk factors for hospitalized patients with COVID-19 in Wuhan, China: an ambispective observational cohort study. Intensive Care Med 46 (7):1472–1474, 2020.
50. Wang GF, Li N, Wu YF, Xie GQ, Lin JT, Huang CB, Xia GG. The COX regression analysis on the use of corticosteroids in the treatment of SARS. Natl Med J China 84 (13):1073–1078, 2004.
51. Wang DW, Yin YM, Hu C, Liu X, Zhang XG, Zhou SL, Jian MZ, Xu HB, Prowle J, Hu B, et al. Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China. Crit Care 24 (1):188, 2020.
52. Wang D, Wang J, Jiang QQ, Yang J, Li J, Gao C, Jiang HW, Ge LT, Liu YM. No clear benefit to the use of corticosteroid as treatment in adult patients with coronavirus disease 2019: a retrospective cohort study. medRxiv 2020.
53. Tu WJ, Cao JL, Yu L, Hu XR, Liu Q. Clinicolaboratory study of 25 fatal cases of COVID-19 in Wuhan. Intensive Care Med 46 (6):1117–1120, 2020.
54. Tomazini BM, Maia IS, Cavalcanti AB, Berwanger O, Rosa RG, Veiga VC, Avezum A, Lopes RD, Bueno FR, Silva MVAO, et al. Effect of dexamethasone on days alive and ventilator-free in patients with moderate or severe acute respiratory distress syndrome and COVID-19: the CoDEX randomized clinical trial. JAMA 324:1307–1316, 2020.
55. Shi Q, Zhang XY, Jiang FJ, Zhang XZ, Hu NH, Bimu CB, Feng JR, Yan S, Guan YJ, Xu DX, et al. Clinical characteristics and risk factors for mortality of COVID-19 patients with diabetes in Wuhan, China: a two-center, retrospective study. Diabetes Care 43 (7):1382–1391, 2020.
56. Shang J, Du RH, Lu QF, Wu JH, Xu SB, Ke ZH, Cai ZF, Gu YY, Huang Q, Zhan Y, et al. The treatment and outcomes of patients with COVID-19 in Hubei, China: a multicentered, retrospective, observational study. Lancet 2020.
57. Ruiz-Irastorza G, Pijoan JI, Bereciartua E, Dunder S, Dominguez J, Garcia-Escudero P, Rodrigo A, Gomez-Carballo C, Varona J, Guio L, et al. Second week methyl-prednisolone pulses improve prognosis in patients with severe coronavirus disease 2019 pneumonia: an observational comparative study using routine care data. PLoS One 15 (9):e0239401, 2020.
58. Rubio-Rivas M, Ronda M, Padulles A, Mitjavila F, Riera-Mestre A, García-Forero C, Iriarte A, Mora JM, Padulles N, Gonzalez M, et al. Beneficial effect of corticosteroids in preventing mortality in patients receiving tocilizumab to treat severe COVID-19 illness. Int J Infect Dis 101:290–297, 2020.
59. Rodriguez-Bano J, Pachon J, Carratala J, Ryan P, Jarrin I, Yllescas M, Arribas JR, Berenguer J. Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19). Clin Microbiol Infect 27 (2):244–252, 2021.
60. Poblador-Plou B, Carmona-Pirez J, Ioakeim-Skoufa I, Poncel-Falco A, Bliek-Bueno K, Cano-Del Pozo M, Gimeno-Feliu LA, Gonzalez-Rubio F, Aza-Pascual-salcedo M, Bandres-Liso AC, et al. Baseline chronic comorbidity and mortality in laboratory-confirmed COVID-19 cases: results from the PRECOVID study in Spain. Int J Environ Res Public Health 17 (14):1–14, 2020.
61. Peng J, Hou JL, Guo YB, Liu DL, Feng XR, Zhu YF, Chen JJ, Jiang RL, Chen YP. Analysis of the effect of glucocorticoid treatment on severe acute respiratory syndrome. Med J Chin PLA 29 (9):752–753, 2004.
62. Nguyen Y, Corre F, Honsel V, Curac S, Zarrouk V, Burtz CP, Weiss E, Moyer JD, Gauss T, Gregory J, et al. A nomogram to predict the risk of unfavourable outcome in COVID-19: a retrospective cohort of 279 hospitalized patients in Paris area. Ann Med 52 (7):367–375, 2020.
63. Mikulska M, Nicolini LA, Signori A, Di Biagio A, Sepulcri C, Russo C, Dettori S, Berruti M, Sormani MP, Giacobbe DR, et al. Tocilizumab and steroid treatment in patients with COVID-19 pneumonia. PLoS One 14 (8):1–16, 2020.
64. Meng QH, Dong PL, Guo YB, Zhang K, Liang LC, Hou W, Dong JL. Use of glucocorticoid in treatment of severe acute respiratory syndrome cases. Chin J Prev Med 37 (4):233–235, 2003.
65. Majmundar M, Kansara T, Lenik JM, Park H, Ghosh K, Doshi R, Shah P, Kumar A, Amin H, Chaudhari S, et al. Efficacy of corticosteroids in non-intensive care unit patients with COVID-19 pneumonia from the New York metropolitan region. medRxiv 15 (9):e0238827, 2020.
66. Ma YM, Zeng HH, Zhan ZJ, Lu HH, Zeng ZH, He CJ, Liu XM, Chen C, Qin QW, He J, et al. Corticosteroid use in the treatment of COVID-19: a multicenter retrospective study in Hunan, China. Front Pharmacol 11:1198, 2020.
67. Ma Q, Qi D, Deng XY, Yuan GD, Tian WG, Cui Y, Yan XF, Wang DX. Corticosteroid therapy for patients with severe novel Coronavirus disease. Eur Rev Med Pharmacol Sci 24 (15):8194–8201, 2020.
68. Ma FF. A study on application value of glucocorticoids in the treatment of SARS. Huazhong Univ Sci Tech 2008.
69. Lu XF, Chen TG, Wang Y, Wang J, Yan FR. Adjuvant corticosteroid therapy for critically ill patients with COVID-19. Crit Care 24 (1):241, 2020.
70. Liu ZB, Li X, Fan GH, Zhou F, Wang YM, Huang LX, Yu JP, Yang LN, Shang LH, Xie K, et al. Low-to-moderate dose corticosteroids treatment in hospitalized adults with COVID-19. Clin Microbiol Infect 27:112–117, 2020.
71. Liu YL, Sun WW, Li J, Chen LK, Wang YJ, Zhang LJ, Yu L. Clinical features and progression of acute respiratory distress syndrome in coronavirus disease. medRxiv 2020.
72. Liu W, Tao ZW, Wang L, Yuan ML, Liu K, Zhou L, Wei S, Deng Y, Liu J, Liu HG, et al. Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease. Chin Med J (Engl) 133 (9):1032–1038, 2020.
73. Liu J, Zhang S, Wu Z, Shang Y, Dong X, Li G, Zhang LD, Chen YZ, Ye XF, Du HX, et al. Clinical outcomes of COVID-19 in Wuhan, China: a large cohort study. Ann Intensive Care 10 (1):99, 2020.
74. Li XC, Xu SY, Yu MQ, Wang K, Tao Y, Zhou Y, Shi J, Zhou M, Wu B, Yang ZY, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol 146:110–118, 2020.
75. Li Q, Li WX, Jin YP, Xu W, Huang CL, Li L, Huang YX, Fu QC, Chen L. Efficacy evaluation of early, low-dose, short-term corticosteroids in adults hospitalized with non-severe COVID-19 pneumonia: a retrospective cohort study. Infect Dis Ther 9:823–836, 2020.
76. Li LL, Yang L, Gui S, Pan F, Ye TH, Liang B, Hu Y, Zheng CS. Association of clinical and radiographic findings with the outcomes of 93 patients with COVID-19 in Wuhan, China. Theranostics 10 (14):6113–6121, 2020.
77. Li JL, Xu G, Yu HP, Peng X, Luo YW, Cao CA. Clinical characteristics and outcomes of 74 patients with severe or critical COVID-19. Am J Med Sci 360 (3):229–235, 2020.
78. Lew TW, Kwek TK, Tai D, Earnest A, Loo S, Singh K, Kwan KM, Chan Y, Yim CF, Bek SL, et al. Acute respiratory distress syndrome in critically ill patients with severe acute respiratory syndrome. JAMA 290 (3):374–380, 2003.
79. Lee JY, Kim HA, Huh K, Hyun M, Rhee JY, Jang S, Kim JY, Peck KR, Chang HH. Risk factors for mortality and respiratory support in elderly patients hospitalized with COVID-19 in Korea. J Korean Med Sci 35 (23):e223, 2020.
80. Lau EHY, Cowling BJ, Muller MP, Ho LM, Tsang T, Lo SV, Louie M, Leung GM. Effectiveness of ribavirin and corticosteroids for severe acute respiratory syndrome. Am J Med 122 (12):1150.e11–1150.e21, 2009.
81. Krishnan S, Patel K, Desai R, Sule A, Paik P, Miller A, Barclay A, Cassella A, Lucaj J, Royster Y, et al. Clinical comorbidities, characteristics, and outcomes of mechanically ventilated patients in the State of Michigan with SARS-CoV-2 pneumonia. J Clin Anesth 67:110005, 2020.
82. Kevorkian JP, Riveline JP, Vandiedonck C, Girard D, Galland J, Feron F, Gautier JF, Megarbane B. Early short-course corticosteroids and furosemide combination to treat non-critically ill COVID-19 patients: an observational cohort study. J Infect 82:e22–e24, 2020.
83. Keller MJ, Kitsis EA, Arora S, Chen JT, Agarwal S, Ross MJ, Tomer Y, Southern W. Effect of systemic glucocorticoids on mortality or mechanical ventilation in patients with COVID-19. J Hosp Med 15 (8):489–493, 2020.
84. Ji JJ, Zhang JX, Shao ZY, Xie QF, Zhong L, Liu ZF. Glucocorticoid therapy does not delay viral clearance in COVID-19 patients. Crit Care 24 (1):565, 2020.
85. Jeronimo CMP, Farias MEL, Val FFA, Sampaio VS, Alexandre MAA, Melo GC, Safe IP, Borba MGS, Abreu-Netto RL, Maciel ABS, et al. Methylprednisolone as adjunctive therapy for patients hospitalized with COVID-19 (Metcovid): a randomised, double-blind, phase IIb, placebo-controlled trial. Clin Infect Dis 2020; ciaa1177.
86. Huang R, Zhu CW, Jian W, Xue L, Li CY, Yan XM, Huang SP, Zhang B, Zhu L, Xu TM, et al. Corticosteroid therapy is associated with the delay of SARS-CoV-2 clearance in COVID-19 patients. Eur J Pharmacol 2020; 173556.
87. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 382:1708–1720, 2020.
88. Giacomelli A, Ridolfo AL, Milazzo L, Oreni L, Bernacchia D, Siano M, Bonazzetti C, Covizzi A, Schiuma M, Passerini M, et al. 30-day mortality in patients hospitalized with COVID-19 during the first wave of the Italian epidemic: a prospective cohort study. Pharmacol Res 158:104931, 2020.
89. Feng XB, Li PY, Ma L, Liang H, Lei J, Li WQ, Wang K, Song Y, Li S, Yang W, et al. Clinical characteristics and short-term outcomes of severe patients with COVID-19 in Wuhan, China. Front Med 7:491, 2020.
90. Ding C, Feng XW, Chen YF, Yuan J, Yi P, Li YT, Ni Q, Zou RR, Li XH, Sheng JF, et al. Effect of corticosteroid therapy on the duration of SARS-CoV-2 clearance in patients with mild COVID-19: a retrospective cohort study. Infect Dis Ther 9:943–952, 2020.
91. Dequin PF, Heming N, Meziani F, Plantefeve G, Voiriot G, Badie J, Francois B, Aubron C, Ricard JD, Ehrmann S, et al. Effect of hydrocortisone on 21-day mortality or respiratory support among critically ill patients with COVID-19: a randomized clinical trial. JAMA 324:1298–1306, 2020.
92. Deng Y, Liu W, Liu K, Fang YY, Shang J, Zhou L, Wang K, Leng F, Wei S, Chen L, et al. Clinical characteristics of fatal and recovered cases of coronavirus disease 2019 in Wuhan, China: a retrospective study. Chin Med J (Engl) 133 (11):1261–1267, 2020.
93. Corral-Gudino L, Bahamonde A, Arnaiz-Revillas F, Gómez-Barquero J, Abadía-Otero J, García-Ibarbia C, Mora V, Cerezo-Hernández A, Hernández JL, López-Muñíz G, et al. GLUCOCOVID: a controlled trial of methylprednisolone in adults hospitalized with COVID-19 pneumonia. medRxiv 2020.
94. Chen T, Wu D, Long CH, Yan WM, Yang DL, Chen G, Ma K, Xu D, Yu HJ, Wang HW, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ 368:m1295, 2020.
95. Chen RC, Tang XP, Tan SY, Liang BL, Wan ZY, Fang JQ, Zhong NS. Treatment of severe acute respiratory syndrome with glucosteroids: the guangzhou experience. Chest 129 (6):1441–1452, 2006.
96. Chen L, Yu JM, He WJ, Chen L, Yuan GL, Dong F, Chen WL, Cao YL, Yang JY, Cai LL, et al. Risk factors for death in 1859 subjects with COVID-19. Leukemia 34 (8):2173–2183, 2020.
97. Chen FY, Sun WW, Sun SR, Li ZY, Wang Z, Yu L. Clinical characteristics and risk factors for mortality among inpatients with COVID-19 in Wuhan, China. Clin Transl Med 10 (2):e40, 2020.
98. Chen FF, Zhong M, Liu Y, Zhang Y, Zhang K, Su DZ, Meng X, Zhang Y. The characteristics and outcomes of 681 severe cases with COVID-19 in China. J Crit Care 60:32–37, 2020.
99. Cao JL, Tu WJ, Cheng WL, Yu L, Liu Yk, Hu XY, Liu Q. Clinical features and short-term outcomes of 102 patients with corona virus disease 2019 in Wuhan, China. Clin Infect Dis 71:748–755, 2020.
100. Brenner EJ, Ungaro RC, Gearry RB, Kaplan GG, Kissous-Hunt M, Lewis JD, Ng SC, Rahier JF, Reinisch W, Ruemmele FM, et al. Corticosteroids, but not TNF antagonists, are associated with adverse COVID-19 outcomes in patients with inflammatory bowel diseases: results from an international registry. Gastroenterology 159:481.e3–491.e3, 2020.
101. Bartoletti M, Marconi L, Scudeller L, Pancaldi L, Tedeschi S, Giannella M, Rinaldi M, Bussini L, Valentini I, Ferravante AF, et al. Efficacy of corticosteroid treatment for hospitalized patients with severe COVID-19: a multicenter study. Clin Microbiol Infect 27:105–111, 2020.
102. Albani F, Fusina F, Granato E, Capotosto C, Ceracchi C, Gargaruti R, Santangelo G, Schiavone L, Taranto MS, Tosati C, et al. Effect of corticosteroid treatment on 1376 hospitalized COVID-19 patients: a cohort study. medRxiv 2020.
103. Aggarwal S, Garcia-Telles N, Aggarwal G, Lavie C, Lippi G, Henry BM. Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): early report from the United States. Diagnosis 7 (2):91–96, 2020.
104. Cano EJ, Fuentes XF, Campioli CC, O’Horo JC, Saleh OA, Odeyemi Y, Yadav H, Temesgen Z. Impact of corticosteroids in COVID-19 outcomes: systematic review and meta-analysis. Chest 159 (3):1019–1040, 2021.
105. Hasan SS, Capstick T, Ahmed R, Kow CS, Mazhar F, Merchant HA, Zaidi STR. Mortality in COVID-19 patients with acute respiratory distress syndrome and corticosteroids use: a systematic review and meta-analysis. Expert Rev Respir Med 14:1149–1163, 2020.
106. Siemieniuk RA, Bartoszko JJ, Ge L, Zeraatkar D, Izcovich A, Pardo-Hernandez H, Rochwerg B, Lamontagne F, Han MA, Kum E, et al. Drug treatments for covid-19: living systematic review and network meta-analysis. BMJ 370:m2980, 2020.
107. Sterne JAC, Murthy S, Diaz JV, Slutsky AS, Villar J, Angus DC, Annane D, Azevedo LCP, Berwanger O, Cavalcanti AB, et al. W.H.O. Rapid Evidence Appraisal for COVID-19 Therapies Working Group. Association between administration of systemic corticosteroids and mortality among critically ill patients with COVID-19: a meta-analysis. JAMA 324:1330–1341, 2020.
108. Ye ZK, Wang Y, Colunga-Lozano LE, Prasad M, Tangamornsuksan W, Rochwerg B, Yao L, Motaghi S, Couban RJ, Ghadimi M, et al. Efficacy and safety of corticosteroids in COVID-19 based on evidence for COVID-19, other coronavirus infections, influenza, community-acquired pneumonia and acute respiratory distress syndrome: a systematic review and meta-analysis. CMAJ 192 (27):E756–E767, 2020.
109. Gangopadhyay KK, Mukherjee JJ, Sinha B, Ghosal S. The role of corticosteroids in the management of critically ill patients with coronavirus disease 2019 (COVID-19): a meta-analysis. medRxiv 2020.
110. Lee KH, Yoon S, Jeong GH, Kim JY, Han YJ, Hong SH, Ryu S, Kim JS, Lee JY, Yang JW, et al. Efficacy of corticosteroids in patients with SARS, MERS and COVID-19: a systematic review and meta-analysis. J Clin Med 9 (8):2392, 2020.
111. Li H, Chen CX, Hu F, Wang JJ, Zhao QY, Gale RP, Liang Y. Impact of corticosteroid therapy on outcomes of persons with SARS-CoV-2, SARS-CoV, or MERS-CoV infection: a systematic review and meta-analysis. Leukemia 34:1503–1511, 2020.
112. Lu SY, Zhou Q, Huang LP, Shi QL, Zhao SY, Wang ZJ, Li WG, Tang YY, Ma YF, Luo XF, et al. Effectiveness and safety of glucocorticoids to treat COVID-19: a rapid review and meta-analysis. Ann Transl Med 8 (10):627, 2020.
113. Tlayjeh H, Mhish OH, Enani MA, Alruwaili A, Tleyjeh R, Thalib L, Hassett L, Arabi YM, Kashour T, Tleyjeh IM. Association of corticosteroids use and outcomes in COVID-19 patients: a systematic review and meta-analysis. J Infect Public Health 13 (11):1652–1663, 2020.
114. Wang YS, Ao GY, Qi X, Zeng J. The influence of corticosteroid on patients with COVID-19 infection: a meta-analysis. Am J Emerg Med 23:S0735-6757(20)30528-3, 2020.
115. Yousefifard M, Ali KM, Aghaei A, Zali A, Neishaboori AM, Zarghi A, Safari S, Hashemi B, Forouzanfar MM, Hosseini M. Corticosteroids on the management of coronavirus disease 2019 (COVID-19): a systemic review and meta-analysis. Iran J Public Health 49 (8):1411–1421, 2020.
116. Budhathoki P, Shrestha DB, Rawal E, Khadka S. Corticosteroids in COVID-19: Is it rational? a systematic review and meta-analysis. SN Compr Clin Med 2020; 1–21.
117. Pei L, Zhang S, Huang LX, Geng XQ, Ma LH, Jiang WW, Li WF, Chen DC. Antiviral agents, glucocorticoids, antibiotics, and intravenous immunoglobulin usage in 1142 patients with coronavirus disease 2019: a systematic review and meta-analysis. Pol Arch Intern Med 130:726–733, 2020.
118. Sarkar S, Khanna P, Soni KD. Are the steroids a blanket solution for COVID-19? A systematic review and meta-analysis. J Med Virol 93 (3):1538–1547, 2021.
119. Yang ZW, Liu JL, Zhou YJ, Zhao XX, Zhao Q, Liu J. The effect of corticosteroid treatment on patients with coronavirus infection: a systematic review and meta-analysis. J Infect 81:e13–e20, 2020.
120. Abdulamir AS, Hafidh RR. The possible immunological pathways for the variable immunopathogenesis of COVID-19 infections among healthy adults, elderly and children. Electron J Gen Med 17 (4):em202, 2020.
121. Asselta R, Paraboschi EM, Mantovani A, Duga S. ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy. Aging 12 (11):10087–10098, 2020.
122. Caruso F, Rossi M, Pedersen JZ, Incerpi S. Computational studies reveal mechanism by which quinone derivatives can inhibit SARS-CoV-2. Study of embelin and two therapeutic compounds of interest, methyl prednisolone and dexamethasone. J Infect Public Health 13:1868–1877, 2020.
123. Rana MA, Hashmi M, Qayyum A, Pervaiz R, Saleem M, Munir MF, Ullah Saif MM. Comparison of efficacy of dexamethasone and methylprednisolone in improving PaO2/FiO2 ratio among COVID-19 patients. Cureus 12 (10):e10918, 2020.
124. Russell CD, Millar JE, Baillie JK. Clinical evidence does not support corticosteroid treatment for 2019-nCoV lung injury. Lancet 395 (10223):473–475, 2020.
125. Lansbury LE, Rodrigo C, Leonardi-Bee J, Nguyen-Van-Tam J, Shen Lim W. Corticosteroids as adjunctive therapy in the treatment of influenza: an updated Cochrane systematic review and meta-analysis. Crit Care Med 48 (2):e98–e106, 2020.
Keywords:

COVID-19; glucocorticoids treatment; mortality; SARS; ARDS; acute respiratory distress syndrome; BNP; brain natriuretic peptide; CI; confidence interval; COVID-19; coronavirus disease 2019; CRP; C-reactive protein; cTnI; cardiac troponin I; cTnT; cardiac troponin T; HRs; hazard ratios; ICU; intensive care unit; LDH; lactate dehydrogenase; MOOSE; meta-analysis of observational studies in epidemiology; NOS; Newcastle-Ottawa-Scale; ORs; odds ratios; PI; prediction interval; PRISMA; preferred reporting items for systematic reviews and meta-analyses; RCT; randomized controlled trial; RRs; risk ratios; SARS; severe acute respiratory syndrome

Supplemental Digital Content

Copyright © 2021 by the Shock Society