key: cord-0973755-9utqo1ev
authors: Shao, Shuai; Wang, Yishan; Kang, Hanyujie; Tong, Zhaohui
title: Effect of convalescent blood products for patients with severe acute respiratory infections of viral etiology: A systematic review and meta-analysis
date: 2020-09-28
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2020.09.1443
sha: c718acecec9b3a7cc2f2b2d5f77c5b564a8d9e68
doc_id: 973755
cord_uid: 9utqo1ev

OBJECTIVES: The aim of this study was to determine whether convalescent blood products (CBPs) offer a survival advantage for patients with severe acute respiratory infections of viral etiology. METHODS: Up-to-date trials were identified by the authors through searches of the MEDLINE, Embase, Cochrane Library, Web of Science, ClinicalTrials.gov, and medRxiv databases from inception up to September 14, 2020. Meta-analyses were performed using a random-effects model. RESULTS: According to the observational studies, patients who received CBPs showed a decline in all-cause mortality compared with patients who did not receive CBPs (odds ratio (OR) 0.36, 95% confidence interval (CI) 0.23–0.56; p < 0.00001). However, the randomized controlled trials (RCTs) showed no difference between the intervention group and the control group regarding all-cause mortality (OR 0.82, 95% CI 0.57–1.19; p = 0.30). The use of CBPs did not increase the risk of adverse events (OR 0.88, 95% CI 0.60–1.29; p = 0.51). Using CBPs earlier compared with using CBPs later was associated with a significant reduction in all-cause mortality (OR 0.18, 95% CI 0.08–0.40; p < 0.0001). CONCLUSIONS: Based on the outcomes of RCTs, CBPs may not decrease all-cause mortality. Furthermore, compared with later initiation of CBP therapy, earlier initiation of this therapy may decrease the rate of mortality.

At the time of writing, more than 29 million people had been diagnosed with coronavirus disease 2019 worldwide in the ongoing pandemic, which started in December 2019, and the overall mortality was 3.1% (Maps & Trends, 2020) . The disease progresses rapidly in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and affected patients may suffer from acute respiratory distress syndrome (ARDS), acute respiratory failure, multi-organ dysfunction, and even death within a short period Guan et al., 2020; Wang et al., 2020; Yang et al., 2020) .

To date, only dexamethasone has been indicated to decrease the mortality of patients with COVID-19 (Horby et al., 2020) . Current management consists of supportive therapy, including oxygen supplementation, antibiotics, antifungal treatment, and extracorporeal membrane oxygenation (ECMO) (Poston et al., 2020; Onder et al., 2020) . Despite these treatments, hospitalized patients with COVID-19 are still at a high risk of mortality, with rates ranging from 10% to 80% (Guan et al., 2020; Richardson et al., 2020; Zeng et al., 2020; Zhou et al., 2020) .

Convalescent plasma (CP) therapy is currently a treatment option proposed for severely affected COVID-19 patients who are experiencing a more rapid and concerning disease progression. This therapy has been one of the central interventions against COVID-19 in the absence of a vaccine and pharmacological interventions (Roback and Guarner, 2020; Piechotta et al., 2020) . The transfusion of convalescent blood products (CBPs) is a type of passive antibody therapy that has been used among patients since the time of the Spanish flu (1917) (1918) (Bloch et al., 2020) . Antibody-rich CBPs represent the only treatment that can be applied immediately among patients with infections of viral etiology, allowing them to obtain antibodies and generate passive immunity. The antibodies from CBPs can bind to the virus directly and neutralize it. At the same time, the antibodies can also clear the virus through opsonization or antibody-dependent cell-mediated cytotoxicity (ADCC).

Recently, several observational studies have suggested that CP could decrease the risk of mortality among patients with COVID-19 (Abolghasemi et al., 2020; Duan et al., 2020) . However, this clinical benefit was not found in a randomized controlled trial (RCT) . Many previous studies have tested the safety and clinical treatment effect of CP among patients with other viral diseases, such as severe acute respiratory syndrome (SARS), influenza, and Ebola hemorrhagic fever (EBHF) (Anon., 2020).

Due to the urgency of the epidemic, people urgently want to know whether CBPs are effective for patients with severe acute respiratory infections (SARI) of viral etiology, especially for patients with COVID-19. However, in order to develop suggestions for doctors regarding the transfusion of CBPs in patients with COVID-19, there is a need to collect and pool the results of eligible studies comprehensively. Therefore, a series of systematic reviews was performed. There is currently little direct evidence to assess the efficacy and safety of CBPs among patients with COVID-19. As the route of disease transmission and clinical features are similar in COVID-19, SARS, Middle East respiratory syndrome (MERS), and influenza, related eligible studies on these SARI were comprehensively included to provide new evidence for the clinical treatment of COVID-19 patients.

This study is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, developed by the Equator Network (Supplementary Material File S1). This work was registered in the International Prospective Register of Systematic Reviews (CRD42020172940). Ethical approval was not required.

A systematic search for relevant studies published between January 1, 1918 and September 14, 2020 was performed in the MEDLINE, Embase, Cochrane Library, Web of Science, ClinicalTrials. gov, and medRxiv databases. The search strategy combined concepts related to respiratory diseases of viral etiology (i.e., MERS coronavirus (MERS-CoV), SARS coronavirus (SARS-CoV), and SARS-CoV-2, influenza, human) and CBPs (i.e., CP, convalescent serum, convalescent blood, and immunization, passive) (Supplementary Material File S2). No filter was applied for the type of study or language.

The inclusion criteria were as follows: (1) RCTs or observational studies; (2) patients of any age and sex who had a laboratoryconfirmed or clinically suspected SARI (the definitions of influenza-like illness and severe acute respiratory infection issued by the World Health Organization (WHO) (Fitzner et al., 2018) ; (3) intravenous CP or convalescent serum or convalescent blood or hyperimmune intravenous immunoglobulin (H-IVIG) or a mixture was used in the intervention group; (4) a control group was included, with placebo, no treatment, other treatment, or later initiation of CBPs applied; (5) the donors had to have been diagnosed previously with the corresponding disease.

First, the search results were manually screened by two authors (SS, YSW) independently to identify eligible studies for further analysis. The citations of each included study were also reviewed carefully. Any disagreement was resolved by discussion with a third author (ZHT).

The data extraction was performed by two authors using a double-entry procedure (SS, HYJK). In addition, the results of the data extraction were verified by a third author (YSW). The following data were extracted: author, publication year, country, the number of centers, study method, viral etiology, diagnostic criteria, type of CBP, treatment strategy with CBP, transfusionrelated adverse events, number of patients in each group, quality score, outcome data, and treatment strategy in the intervention and control groups. The risk of bias in eligible RCTs was examined using the Cochrane Collaboration risk of bias tool (Higgins et al., 2011; Cochrane Training, 2020 ). The quality of observational studies was assessed using the Newcastle-Ottawa Scale (NOS) (range 0 À 9 stars) (Ottawa Hospital Research Institute, 2020).

The primary outcome was all-cause mortality. Secondary outcomes included the timing of initiation of CBPs (earlier versus later), adverse events, length of intensive care unit (ICU) stay, length of hospital stay, and days on mechanical ventilation (MV).

Continuous variables were recorded as the mean AE standard deviation (SD). Values for categorical variables were recorded as the odds ratio (OR) with 95% confidence interval (CI). The metaanalyses were performed using random-effects models. A twotailed p-value of less than 0.05 was considered statistically significant for all results. A correction factor (1.0) was applied to zero-event trials to enforce the effect of the OR (Sweeting et al., 2004) . The I 2 derived from Chi-square tests was applied to assess the heterogeneity between trials, with a value of >50% regarded as indicating high heterogeneity. Univariate meta-regression using a random-effects model analysis was used to reveal the potential sources of heterogeneity. The publication bias for the outcome, in analyses that included more than five studies, was judged by funnel plot and Egger's test (Song and Gilbody, 1998) . The quality of evidence for the outcomes was further assessed according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework. A trial sequential analysis (TSA) was also performed, in which it was chosen to calculate the required information size by using an 18% relative risk reduction (RRR) for falls (calculated from the eight RCTs Beigel et al., 2019; Beigel et al., 2017; Davey et al., 2019; Hung et al., 2013; Avendano-Sola et al., 2020; Agarwal et al., 2020) ). The control group rate was assumed to be 10.3%. The TSA was performed with a two-sided alpha of 0.05 and a beta of 0.20 (power 80%) to limit type I errors and type II errors. The statistical analyses were completed using Review Manager version 5.3, Stata version 15.1, GRADE Profiler version 3.6, and TSA 0.9.5.10 Beta.

The following variables were selected before the subgroup analysis was undertaken to explore the potential sources of heterogeneity: the type of CBP, the different types of viral disease, and the study quality score. A test of interaction was performed to judge the differences in treatment effect across these subgroups (Sun et al., 2014; Lee et al., 2018; Udell et al., 2013) . When I 2 !50%, sensitivity analyses were performed by sequentially removing one study at a time to identify the studies that influenced the results significantly.

A flow chart of the literature search and selection process is shown in Figure 1 . The Insight Flu 005 trial was not included in the present exploratory meta-analysis due to the lack of sufficient data for the outcomes that were required (Anon., 2020).

The characteristics of the included studies are shown in Table 1 . The viral diseases that were studied included Spanish influenza A (H1N1) (Gould, 1919; Kahn, 1919; O'Malley and Hartman, 1919; Ross and Hund, 1919; Sanborn, 1920; Stoll, 1919) , SARS (Cheng et al., 2005; Soo et al., 2004; Zhou et al., 2003) , EBHF (Sahr et al., 2017; van Griensven et al., 2016) , influenza A (H1NI) pdm09 (Chan et al., 2010; Hung et al., 2011; Hung et al., 2013) , avian influenza A (H5N1) (Yu et al., 2008) , multiple viral etiologies (Yu et al., 2008) (e.g., patients with influenza A(H1N1) and patients with influenza A(H3N2) at the same time (Beigel et al., 2019) ), and COVID-19 (Abolghasemi et al., 2020; Avendano-Sola et al., 2020; Zeng et al., 2020) . The median age of the patients in all studies was 53.0 years (interquartile range (IQR) 44.3-60.2 years) (Duan et al., 2020; Hung et al., 2011; Hung et al., 2013; Soo et al., 2004; van Griensven et al., 2016; Yu et al., 2008) (Tables 2a and 2b) .

In terms of the risk of bias of the nine RCTs included, seven RCTs were categorized as having a high risk of bias Beigel et al., 2017; Davey et al., 2019; Hung et al., 2013; Avendano-Sola et al., 2020) and the other two as having an unclear risk of bias (Anon., 2020; Beigel et al., 2019) (Supplementary Material File S3 and File S4) . More details are shown in Table 3 . The quality of the 19 observational studies was assessed according to the NOS. Seven studies (Abolghasemi et al., 2020; Duan et al., 2020; Cheng et al., 2005; Sahr et al., 2017; Soo et al., 2004; van Griensven et al., 2016; Zeng et al., 2020) were classified as high quality and 12 studies (Chan et al., 2010; Gould, 1919; Hung et al., 2011; Kahn, 1919; O'Malley and Hartman, 1919; Ross and Hund, 1919; Sanborn, 1920; Stoll, 1919; Yu et al., 2008; Zhou et al., 2003) were classified as moderate quality (Supplementary Material File S5). Six studies compared 'earlier' treatment with 'later' treatment in SARI patients (Cheng et al., 2005; Hung et al., 2013; Maclachlan and Fetter, 1918; Ross and Hund, 1919; Sanborn, 1920; Stoll, 1919) . All of them used a time-point to define 'earlier' and 'later,' but the specific time-point cut-offs were not the same among the studies. Specifically, the median time-point of 'earlier' treatments when patients received CBPs after symptom onset was 3.8 days (IQR 2.1-6.5 days) (Cheng et al., 2005; Hung et al., 2013; Maclachlan and Fetter, 1918; Ross and Hund, 1919; Sanborn, 1920; Stoll, 1919) . As a result, earlier treatment was defined as receiving CBPs within 4 days of illness onset and later treatment was defined as receiving CBPs at !4 days following illness onset.

Two studies provided the mean total volume of CBP transfusion (125 ml (O'Malley and Hartman, 1919) and 400 ml (Yu et al., 2008) ). The other six studies described the protocol of CBP transfusion clearly in the methods section (Abolghasemi et al., 2020; Duan et al., 2020; Chan et al., 2010; Davey et al., 2019; Hung et al., 2011; Sahr et al., 2017; Zhou et al., 2003; Gharbharan et al., 2020; Agarwal et al., 2020) . The median volume of CBP was 400 ml (IQR 200-500 ml). A low dose was defined as a total volume of less than 200 ml, because one unit of CBP was almost 200 ml. Greater volumes were considered a high dose.

The pooled data extracted from the RCTs revealed that there was no significant reduction in all-cause mortality in the intervention group when compared with the control group (OR 0.82, 95% CI 0.57-1.19; p = 0.30; I 2 = 0%) (Figure 2A ) Beigel et al., 2019; Beigel et al., 2017; Davey et al., 2019; Hung et al., 2013; Avendano-Sola et al., 2020; Agarwal et al., 2020) . After the eight studies were divided into COVID-19 and influenza subgroups, CBPs did not significantly reduce all-cause mortality either in patients with COVID-19 ( File S6) . However, the data on all-cause mortality extracted from the observational studies revealed a significant decrease in mortality in the intervention group when compared with the control group (OR 0.36, 95% CI 0.23-0.56; p < 0.00001; I 2 = 52%) ( Figure 2B ) (Abolghasemi et al., 2020; Duan et al., 2020; Chan et al., 2010; Gould, 1919; Hung et al., 2011; Kahn, 1919; McGuire and Redden, 1919; Sahr et al., 2017; Soo et al., 2004; Zhou et al., 2003; Zeng et al., 2020) .

A sensitivity analysis was then performed by sequentially omitting each trial. After excluding the trial of McGuire et al. (McGuire and Redden, 1919; McGuire and Redden, 1918) , the results revealed that the heterogeneity decreased from 52% to 14% (OR 0.48, 95% CI 0.35-0.66; p < 0.00001; I 2 = 14%) (Supplementary Material File S7). This may be because the patients in the intervention group and the patients in the control group did not come from the same time period, although they all came from the same hospital. As a result, it was best to exclude this trial to ensure the robustness of the outcome of all-cause mortality (Table 4) .

Potential sources of heterogeneity were explored by subgroup analysis (Figure 3) . The results of the subgroup analysis revealed that CP (OR 0.43, 95% CI 0.25-0.71; p = 0.001; I 2 = 28%), convalescent serum (OR 0.11, 95% CI 0.05-0.23; p < 0.00001; I 2 = 0%), and convalescent blood (OR 0.41, 95% CI 0.18-0.90; p = 0.03; I 2 = 0%) could decrease all-cause mortality when compared with the control group. The interaction test showed that there might be differences between the subgroups of the various types of CBP compared with control group for this outcome (p = 0.002). The type of viral etiology and the quality of the study were not the source of heterogeneity (Supplementary Material File S8) .

The meta-regression regarding all-cause mortality of observational studies observed that the treatment effect was not affected by the dose of CBP (high or low dose) (p = 0.697), publication year (p = 0.329), study sample size (p = 0.945), race (p = 0.896), mean age (p = 0.324), proportion of males (%) (p = 0.117), proportion of pregnant women (%) (p = 0.866), or the proportion of patients under 18 years old (%) (p = 0.535). The funnel plot for RCTs, which 

Redden/1919 

Primary outcomes All-cause mortality in RCTs 8 Beigel et al., 2019; Beigel et al., 2017; Davey et al., 2019; Hung et al., 2013; Avendano-Sola et al., 2020; Gharbharan et al., 2020; Agarwal et al., 2020) (Abolghasemi et al., 2020; Duan et al., 2020; Chan et al., 2010; Gould, 1919; Hung et al., 2011; Kahn, 1919; McGuire and Redden, 1919; McGuire and Redden, 1918; O'Malley and Hartman, 1919; Ross and Hund, 1919; Sahr et al., 2017; Soo et al., 2004; Stoll, 1919; van Griensven et al., 2016; Yu et al., 2008; Zhou et al., 2003; Zeng et al., 2020) 2560 0.36 (0.23, 0.56) 52% <0.00001

Secondary outcomes Earlier versus later 6 (Cheng et al., 2005; Hung et al., 2013; Maclachlan and Fetter, 1918; Ross and Hund, 1919; Sanborn, 1920; Stoll, 1919) 331 0.18 (0.08, 0.40) 39% <0.0001

Adverse events 7 Beigel et al., 2019; Beigel et al., 2017; Davey et al., 2019; Hung et al., 2013; Avendano-Sola et al., 2020; Gharbharan et al., 2020) (Gould, 1919; Kahn, 1919; McGuire and Redden, 1919; McGuire and Redden, 1918; O'Malley and Hartman, 1919; Ross and Hund, 1919; Stoll, 1919) Abolghasemi et al., 2020; Duan et al., 2020; Chan et al., 2010; Hung et al., 2011; O'Malley and Hartman, 1919; Soo et al., 2004; van Griensven et al., 2016; Yu et al., 2008; Zhou et al., 2003; Zeng et al., 2020) Chan et al., 2010; Gould, 1919; Hung et al., 2011; Kahn, 1919; McGuire and Redden, 1919; McGuire and Redden, 1918; O'Malley and Hartman, 1919; Ross and Hund, 1919; Stoll, 1919; Yu et al., 2008; Zhou et al., 2003) 1713 0.31 (0.16, 0.60) 61% 0.11 a High quality 6 (Abolghasemi et al., 2020; Duan et al., 2020; Sahr et al., 2017; Soo et al., 2004; van Griensven et al., 2016; Zeng et al., 2020) compared the CBPs with placebo (or no treatment), showed an absence near the bottom right, but the Egger linear regression test did not show any evidence of potential publication bias (p = 0.077) ( Figure 4A ). The same situation was found for the results of allcause mortality in the observational studies, and the Egger linear regression test did not find any evidence of substantial publication bias (p = 0.195) ( Figure 4B ).

In terms of the optimal timing of initiation of CBPs, the pooled results revealed that there might be an improvement in the 'earlier' group when compared with the 'later' group (OR 0.18, 95% CI 0.08-0.40; p < 0.0001; I 2 = 39%) ( Figure 5 ) (Cheng et al., 2005; Hung et al., 2013; Maclachlan and Fetter, 1918; Ross and Hund, 1919; Sanborn, 1920; Stoll, 1919) .

The pooled analysis revealed no significant difference between the groups in the length of ICU stay (mean difference (MD) 0.35, 95% CI À 0.70 to 1.40; p = 0.51; I 2 = 0%) (Beigel et al., 2019; Beigel et al., 2017; Hung et al., 2013; Agarwal et al., 2020) , length of hospital stay (MD À 1.52, 95% CI À 3.53 to 0.49; p = 0.14; I 2 = 0%) (Beigel et al., 2019; Beigel et al., 2017; Hung et al., 2013) (Supplementary Material File S9), or adverse events (OR 0.88, 95% CI 0.60-1.29; p = 0.51; I 2 = 0%) Beigel et al., 2019; Beigel et al., 2017; Davey et al., 2019; Hung et al., 2013 ; Avendano-Sola et al., 2020; Gharbharan et al., 2020) ( Figure 6 ). However, there was a significant improvement in the intervention group versus the control group regarding days on MV (MD À 4.20, 95% CI À 7.45 to À0.94; p = 0.01; I 2 = 19%) (Beigel et al., 2019; Beigel et al., 2017) (Supplementary Material File S9C) (Beigel et al., 2019; Beigel et al., 2017) .

Visual inspection indicated symmetry in the funnel plots of the secondary outcomes of the optimal timing of initiation of CBPs and adverse events, and the p-value of Egger linear regression was 0.768 and 0.679, respectively (Supplementary Material File S10).

The quality of the evidence for the five outcomes ranged from very low to moderate. The quality of the evidence for all-cause mortality in RCTs was assessed as low (Table 5) . Furthermore, the quality of evidence for all-cause mortality in the observational studies was assessed as very low (Table 5) . Details for the secondary outcomes can be found in Supplementary Material File S11.

A TSA was performed for all-cause mortality for the eight RCTs. The Z-curve of all-cause mortality between the intervention group and the control group did not cross the trial sequential monitoring boundary, the conventional boundary, or the line of estimated information size, revealing that the result may be a false-negative and that more RCTs are needed to prove it (Figure 7 ).

In this meta-analysis, a reduction in all-cause mortality associated with CBPs was found for the observational studies but not for the RCTs. Moreover, the results indicate that earlier treatment, when compared with later treatment, might decrease the all-cause mortality of SARI patients. In terms of days on MV, the pooled results revealed that there might be an improvement for patients receiving CBPs when compared to those not receiving this treatment. The pooled estimates of eligible studies indicated that no significant difference could be found between the groups with regard to the length of ICU stay, length of hospital stay, or risk of adverse events.

Compared with the previous meta-analyses (Luke et al., 2006; Mair-Jenkins et al., 2015) , we completed an up-to-date and comprehensive meta-analysis by including studies published after 2013, especially RCTs published from 2013 to 2019 (Luke et al., 2006; Mair-Jenkins et al., 2015) and seven studies published in 2020 (Abolghasemi et al., 2020; Li et al., 2020; Avendano-Sola et al., 2020; Zeng et al., 2020) .

A recent meta-analysis studied the efficacy and safety of CP (Devasenapathy et al., 2020) . Compared with that study, we included an additional 19 observational studies (Abolghasemi et al., 2020; Duan et al., 2020; Chan et al., 2010; Gould, 1919; Hung et al., 2011; Kahn, 1919; McGuire and Redden, 1919; Sahr et al., 2017; Soo et al., 2004; Zhou et al., 2003; Zeng et al., 2020) and four CBPs, convalescent blood products; CI, confidence interval; OR, odds ratio; RCT, randomized controlled trial. a The basis for the assumed risk (e.g., the median control group risk across studies) is provided in the footnotes below. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI RCTs focused on patients with SARS-CoV-2 infection Avendano-Sola et al., 2020; Agarwal et al., 2020) ; this enabled us to comprehensively evaluate the efficacy of CBPs in patients with SARI of viral etiology. Niveditha et al. (Devasenapathy et al., 2020) included four RCTs, and the pooled results showed that CP did not decrease mortality in the intervention group compared with the control group, which is similar to the result of the present study. However, this finding differs from that for all-cause mortality derived from observational studies. Possible reasons for this difference are as follows. According to the TSA, the RCT analysis might have led to false-negative results, and more patients are needed to clarify the therapeutic effect of CBPs. In addition, three RCTs used H-IVIG with a high hemagglutination inhibition titer (HAI) in the intervention groups (Beigel et al., 2019; Beigel et al., 2017; Davey et al., 2019) . However, although the HAI can indicate the quantity of antibodies, it cannot determine the quality of antibodies very well. At the same time, the HAI in these three studies might not have been high enough to treat patients with SARI of viral etiology (Kanjilal and Mina, 2019) . Also, standard care, including neuraminidase inhibitors, antibiotic treatment, antifungal treatment, etc., was used in both groups, but whether these concomitant therapies could have influenced the clinical outcomes was unclear. Although there might be several limitations in these RCTs, the limitations of observational studies, including the lack of randomization to contemporary control groups, is a far greater concern, and this cannot be ignored. As a result, more high quality and large sample size RCTs should be performed in the future. In theory, CBPs might improve the clinical outcomes of patients by increasing antibody titers, decreasing the viral load, and reducing the levels of inflammatory factors in the patient's body. A recent study observed that five COVID-19 patients, after receiving CP, had higher antibody titers than did pre-transfusion patients (range 40-60 before transfusion and 80-320 on day 7 after transfusion) (Shen et al., 2020) . A study by Zeng et al. observed that all COVID-19 patients had viral clearance by 3 days after they received CP (Zeng et al., 2020) . A similar outcome was found in another study, which showed that 87.2% of the CP group was negative for viral nucleic acid at 72 hours after transfusion, while this rate was only 37.5% in the control group . Moreover, several studies have found that the cytokine storm mediated by interleukin (IL)-2, IL-7, IL-10, G-SCF, IP10, MCP-1, MIP (macrophage inflammatory protein)-1A, and tumor necrosis factor alpha (TNF-α) was the crucial mechanism of disease progression in patients with severe COVID-19 (Huang et al., 2020; Vaninov, 2020; Mehta et al., 2020) . In a cohort study that recruited patients with influenza A(H1N1) pdm09, a subgroup analysis of 44 patients revealed that the corresponding day 5 IL-6, day 5 IL-10, day 5 TNFα, day 7 IL-10, and day 9 IL-10 levels were significantly lower in patients who received CP than in the patients in the control group (Hung et al., 2011) .

Additionally, the present study results indicated that the earlier usage of CBPs could offer a greater improvement for patients with SARI when compared with the later usage of CBPs, which is consistent with the results of previous meta-analyses (Luke et al., 2006; Mair-Jenkins et al., 2015) . The newest study focusing on COVID-19 patients showed that those who received CP before 14 days post-onset of illness had better treatment outcomes than those who received transfusions later (Duan et al., 2020) . This may be because, in the early stage of infection, the body's immune response is not severe, and the tissues and organs are not severely damaged. At this time, the antibody could neutralize the virus' infectivity directly and bring clinical benefits to the patient through antibody-mediated pathways like complement activation and ADCC. Using CBPs later might allow the course of the illness to progress too far for the patient to benefit from the treatment. Although the neutralizing antibody could still bind to the pathogen through the mechanisms mentioned above, the tissues and organs of the patient might have been damaged irreversibly due to virus reproduction and a severe inflammatory reaction. Serious complications, such as sepsis and coagulation dysfunction, may have occurred at the same time.

According to the existing study results, CBPs seem to be safe in treating patients with SARI of viral etiology, and no study has reported life-threatening CBP-related adverse events. Joyner et al. analyzed safety metrics in 5000 hospitalized adults with severe or life-threatening COVID-19 after the transfusion of ABO-compatible CP (Joyner et al., 2020) . Thirty-six patients (<1%) reported severe adverse events (SAEs), and half of them were transfusionassociated circulatory overload (TACO) (seven patients) or transfusion related acute lung injury (TRAIL) (11 patients). Simultaneously, according to the judgment of the treating physician, only two of 18 SAEs were directly related to the transfusion of CP. 'Antibody-dependent enhancement' (ADE) is another concern for the transfusion of CP in COVID-19 patients. This is largely a theoretical risk of severe COVID-19 patients experiencing ADE after previous exposure to one or more strains of the coronavirus with heterogeneity of the antigenic epitope (Tetro, 2020) . In theory, if enough neutralizing antibodies are present in the CP from donors, and the patient who receives the CP is infected with the same SARS-CoV-2 strain of virus, the virus may be destroyed (Ulrich et al., 2020) . However, if the protective neutralizing antibody titer in the CP is low or the recipient is infected with a different SARS-CoV-2 strain (e.g., RBD mutant), low levels of SARS-CoV-2/antibody complexes may be induced (Ulrich et al., 2020; Fu et al., 2020) . This complex could bind to angiotensin-converting enzyme 2 (ACE2), and ADE can subsequently be observed through internalization of the complex and IgG-induced stimulation (Ulrich et al., 2020; Fu et al., 2020) . However, most descriptions of ADE have been in relation to experimental settings without strong clinical support (de Alwis et al., 2020) . The potential threat of ADE needs to be investigated further, especially given the many survivors who have developed immunity.

To our knowledge, this meta-analysis recruited the largest number of relevant studies by far, and seven studies on patients with COVID-19 were included (Abolghasemi et al., 2020; Avendano-Sola et al., 2020; Zeng et al., 2020) . We updated the outcomes, such as the optimal timing of CBP initiation. TSA software was applied in the present study to assess the robustness of the relevant results. However, there are some limitations. First, several eligible studies involved very few patients, so we cannot ignore the possibility of a 'small sample effect,' and their sampling error should be fully considered (Lin, 2018) . In addition, the current results may not be conclusive. The TSA analysis revealed that more patients were required to validate the use of CBPs in patients with SARI. Moreover, three of the RCTs have not been peer-reviewed, which might affect the robustness of the result (Avendano-Sola et al., 2020) . Although this meta-analysis recruited studies including multiple types of viral CBP, which might be non-specific for any viral disease, subgroup analyses were performed to resolve this problem. As we know little about the treatment effects of CP in COVID-19, more high-quality RCTs with a larger sample size are needed to assess the efficacy, safety, optimal time of initiation, and best dose of CP in COVID-19 patients.

Taken together, the low-quality evidence in this study shows that the transfusion of CBPs may not reduce all-cause mortality.

Although the transfusion of CP is associated with a low rate of adverse events, the widespread use of CP in patients should be based on high-quality RCTs. If clinicians decide to transfuse CP to patients, earlier initiation might be better.

Shuai Shao developed the initial idea for this study and conducted a comprehensive search of the databases. Shuai Shao and Yishan Wang were responsible for the study selection. Shuai Shao extracted the data. All authors made contributions to the research design, interpretation of results, and ideas for writing studies. Shuai Shao synthesized and analyzed the data and drafted the manuscript. Yishan Wang, Hanyujie Kang, and Zhaohui Tong reviewed the study and provided suggestions. All authors carefully examined this manuscript and agreed with the ideas presented in the study.

Zhaohui Tong received support for this study from the National Natural Science Foundation of China (grant number 81870004).

Not applicable.

Not applicable.

The datasets generated and/or analyzed during the current study are available in the MEDLINE, Embase, Cochrane Library, Web of Science, ClinicalTrials.gov, and medRxiv databases.

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Zhaohui Tong received support for this study from the National Natural Science Foundation of China (grant number 81870004).

None of the authors has any competing interests.

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.ijid.2020.09.1443.