COVID-19 vaccine immunogenicity among chronic liver disease patients and liver transplant recipients: A meta-analysis

Article information

Clin Mol Hepatol. 2022;28(4):890-911

Publication date (electronic) : 2022 June 3

doi : https://doi.org/10.3350/cmh.2022.0087

Ka Shing Cheung ¹^,²^,^*, Chiu Hang Mok ³^,^*, Xianhua Mao ¹, Ruiqi Zhang ¹, Ivan FN Hung ¹, Wai Kay Seto^,¹^,²^,⁴

, Man Fung Yuen^,¹^,⁴

¹Department of Medicine, Queen Mary Hospital, School of Clinical Medicine, The University of Hong Kong, Hong Kong

²Department of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China

³School of Clinical Medicine, The University of Hong Kong, Hong Kong

⁴State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong

Corresponding author : Man-Fung Yuen Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Pokfulam Road, Hong Kong Tel: +852-22553984, Fax: +852-28162863, E-mail: mfyuen@hkucc.hku.hk

Wai-Kay Seto Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Pokfulam Road, Hong Kong Tel: +852-22556979, Fax: +852-28725828, E-mail: wkseto@hkucc.hku.hk

*The two authors share co-first authorship

Editor: Eun Sun Jang, Seoul National University Bundang Hospital, Korea

Received 2022 April 5; Revised 2022 May 25; Accepted 2022 May 31.

Abstract

Background/Aims

Data of coronavirus disease 2019 (COVID-19) vaccine immunogenicity among chronic liver disease (CLD) and liver transplant (LT) patients are conflicting. We performed meta-analysis to examine vaccine immunogenicity regarding etiology, cirrhosis status, vaccine platform and type of antibody.

Methods

We collected data via three databases from inception to February 16, 2022, and reported pooled seroconversion rate, T cell response and safety data after two vaccine doses.

Results

Twenty-eight (CLD only: 5; LT only: 18; both: 2; LT with third dose: 3) observational studies of 3,945 patients were included. For CLD patients, seroconversion rate ranged between 84% (95% confidence interval [CI], 76–90%) and 91% (95% CI, 83–95%), based predominantly on neutralizing antibody and anti-spike antibody, respectively. Seroconversion rate was 81% (95% CI, 76–86%) in chronic hepatitis B, 96% (95% CI, 93–97%) in non-alcoholic fatty liver disease, 85% (95% CI, 75–91%) in cirrhosis and 85% (95% CI, 78–90%) in non-cirrhosis, 86% (95% CI, 78–92%) for inactivated vaccine and 89% (95% CI, 71–96%) for mRNA vaccine. The pooled seroconversion rate of anti-spike antibody was 66% (95% CI, 55–75%) after two doses of mRNA vaccines and 88% (95% CI, 58–98%) after third dose among LT recipients. T cell response rate was 65% (95% CI, 30–89%). Prevalence of adverse events was 27% (95% CI, 18–38%) and 63% (95% CI, 39–82%) among CLD and LT groups, respectively.

Conclusions

CLD patients had good humoral response to COVID-19 vaccine, while LT recipients had lower response.

Keywords: COVID-19; SARS-CoV-2; Liver transplant; Chronic hepatitis B; Non-alcoholic fatty liver disease

Graphical Abstract

INTRODUCTION

Coronavirus disease 2019 (COVID-19) has affected over 400 million people and caused near nearly 6 million deaths globally as of March 2022 [1]. Vaccination has high efficacy profile against COVID-19 infection using different vaccine platforms, such as mRNA (e.g., BNT162b2 [2], mRNA-1273 [3]), adenoviral vector (e.g., ChAdOx1 nCov-19/AZD1222 [4]), and inactivated vaccines (e.g., CoronaVac [5], BBIBP-CorV [6]). However, these trials had limited data on patients with chronic liver disease (CLD).

CLD is associated with higher risk of adverse outcomes following COVID-19 infection, especially those with liver cirrhosis [7,8]. Immunogenicity and safety of COVID-19 vaccine is a concern in this group of patients, as cirrhosis affects innate and adaptive immune response [9]. A study of 581 subjects receiving inactivated vaccines revealed that the seroconversion rates of neutralizing antibody (Nab) were 76.8%, 78.9%, and 76.7% among non-cirrhosis, compensated and decompensated cirrhosis groups respectively, in comparison with healthy subjects (90.3%) [10]. However, other studies reported a higher seroconversion rate of at least 90% among CLD patients [11,12].

Due to use of immunosuppressants, liver transplant (LT) recipients are at higher risk of severe infection [13], and have attenuated response to vaccinations against other diseases [14]. Lower immunogenicity was reported in LT recipients (73.9%) comparing with cirrhotic patients (100%) and controls (100%) [15]. An even lower seroconversion rate of <50% was reported in some studies [16-21].

The conflicting data of COVID-19 vaccine immunogenicity among CLD patients and LT recipients could be related to significant heterogeneity among studies in terms of CLD etiology, cirrhosis status, vaccine platform and type of antibody measured (including Nab, anti-spike receptor binding domain [RBD] antibody and anti-spike antibody). Currently, Nab level is a surrogate marker of vaccine effectiveness [22] and is predictive of protection from symptomatic COVID-19 infection [23,24]. Although levels of anti-spike antibody correlate with Nab, seropositivity is lower upon measurement of Nab than anti-spike antibody [11,25,26].

We therefore performed a systematic review and meta-analysis to summarize data on vaccine immunogenicity and reactogenicity among patients with liver diseases with stratification according to etiology, cirrhosis status, vaccine platform and type of antibody measured.

MATERIALS AND METHODS

Data sources and searches

We searched electronic databases MEDLINE (OVID), EMBASE, and Cochrane Library from inception to February 16, 2022. Keywords include liver disease, LT, organ transplant, COVID-19, vaccination. The search details can be found in Appendix 1. This review was conducted and reported in consonance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

Study selection

Two reviewers (KSC, CHM) screened the titles and abstracts independently for inclusion. Full texts were retrieved if they met the inclusion criteria and assessed independently, and dissonance was resolved by WKS and MFY. Inclusion criteria included (1) study population: CLD patients and LT recipients; (2) intervention: COVID-19 vaccines (including CoronaVac, BBIBP-CorV, WIBP-CorV, BNT162b2, mRNA-1273, AZD1222); (3) study design: randomized controlled trials and observational studies; and (4) primary outcome: seroconversion rate of either Nab or anti-spike antibody. Secondary outcomes are T cell immune response and frequency of adverse events.

Exclusion criteria included (i) age <18 years; (ii) history of COVID-19 infection; and (iii) non-original studies, such as systematic reviews, meta-analysis, review articles, or guidelines. A summary of studies identified, included, and excluded is shown in PRISMA flow diagram (Supplementary Fig. 1).

Data extraction and quality assessment

For eligible studies, we recorded the first author, site of study, study duration, sample size, age, sex, causes of CLD and LT, COVID-19 vaccine type administered, antibody type measured, time interval of antibody measurement from second dose of vaccination, method of antibody test, and cut-off of antibody level regarded as seropositive (Table 1).

Table 1.

Background characteristics of the included studies

The quality of observational studies was assessed using Newcastle-Ottawa scale (NOS). Risk of bias was categorized into three groups: low risk (7–9 points), moderate risk (4–6 points), and high risk (<4 points) [27].

Data analysis

All statistical analyses were conducted in R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria) statistical software. Continuous variables were expressed as median (interquartile range [IQR]) or mean±standard deviation). The pooled rate of seroconversion and adverse events were expressed as proportion and 95% confidence interval (95% CI) using random effects model, and was presented as Forest plot. A P-value of <0.05 was used to define statistical significance. We used Cochran Q test to detect heterogeneity among studies, with a P-value <0.10 indicating significant heterogeneity. We calculated I² statistic to measure proportion of total variation in study estimates attributed to heterogeneity. I² values of ≥50% and ≥75% indicate substantial and considerable heterogeneity, respectively [28]. Meta-regression analysis was used to examine association between background characteristics of the included studies and pooled seroconversion rates [29].

We assessed publication bias by funnel plot and Egger regression. Publication bias was considered significant if P-value of Egger regression is <0.1 [30]. The trim-and-fill method was used to adjust for publication bias, if present, which re-estimated the effect size after imputing potentially missing studies.

Subgroup analysis was performed according to type of antibody tested, method of antibody test (electrochemiluminescence immunoassay analyzer [ECLIA], enzyme-linked immunosorbent assay [ELISA], and chemiluminescence immunoassays [CLIA]), age (with a cut-off of 60 years), etiology of CLD, cirrhosis status, vaccine platform, individual vaccine type, use of multiple immunosuppressants, and region, where applicable.

RESULTS

Study characteristics of meta-analysis

Supplementary Figure 1 depicts the study selection process. Of the 3,590 studies identified, 28 (CLD only: 5, LT only: 18, both CLD and LT: 2; LT with third dose vaccine: 3) are included in the meta-analysis with 3,945 subjects. The characteristics of included studies are shown in Table 1 (for CLD patients and LT recipients receiving two doses of vaccine) and Supplementary Table 1 (for LT recipients receiving third dose). For CLD patients, the median age was 53.8 years (IQR, 43.0–64.4 years), and 62.1% were male. For LT recipients, the median age was 63.0 years (IQR, 59.0–65.6 years), and 64.0% were male. All studies scored at least six stars in NOS, indicating low to moderate risk of bias with satisfactory quality (Supplementary Table 1).

Meta-analysis for CLD patients

Humoral immune response

There are seven observational studies with 1,452 subjects (studies reporting both Nab and anti-spike antibody: 3; Nab only: 2; anti-spike antibody only: 2) (Table 1). In Nab predominance forest plot (Nab: 5; anti-spike antibody: 2), pooled seroconversion rate was 84% (95% CI, 76–90%) with considerable heterogeneity among the studies (P<0.01; I²=91%) (Fig. 1). In anti-spike antibody predominance forest plot (anti-spike antibody: 5; Nab: 2), pooled seroconversion rate was 91% (95% CI, 83–95%) with considerable hereogeneity (P<0.01; I²=93%) (Fig. 1).

Figure 1.

Pooled seroconversion rate in chronic liver disease. CI, confidence interval.

The funnel plot appeared to be have some asymmetry for studies with either anti-spike antibody (P=0.038 by Egger test) or neutralizing antibody predominance (P=0.012 by Egger test), indicating publication bias (Supplementary Fig. 2). Trim and fill-method was used to adjust for publication bias, and the pooled seroconversion rate was 83% (95% CI, 71–90%) for Nab predominance analysis and 82% (95% CI, 61–93%) for anti-spike antibody predominance analysis.

Meta-regression analysis showed significant association between seroconversion of Nab and etiology of liver disease (P<0.001) and a trend for method of antibody test (P=0.053 for ECLIA vs. ELISA) but not other factors (Supplementary Fig. 3).

Antibody type

Pooled seroconversion rate of Nab and anti-spike antibody was 84% (95% CI, 74–91%) and 92% (95% CI, 82–97%), respectively (Fig. 2).

Figure 2.

Pooled seroconversion rate in chronic liver disease according to antibody type. CI, confidence interval; Ab, antibody.

Method of antibody test

There were four studies on CLIA, two on ELISA and one on ECLIA. Seroconversion rate was 89% (95% CI, 77–95%), 88% (95% CI, 82–92%), 76% (95% CI, 69–82%) in CLIA, ELISA and ECLIA, respectively (Supplementary Fig. 4).

Age

There were two studies with median age ≥60 years and five studies with median age <60 years. Seroconversion rate was 85% (95% CI, 64–94%) and 88% (95% CI, 79–93%) in the older and younger age group, respectively (Supplementary Fig. 5).

Etiology of liver disease and cirrhosis status

We used 80% as cut-off for classifying the major etiology of a study. There were three studies on chronic hepatitis B (CHB) infection (two studies with 100% CHB [25,26] and one with 87.9% [10]) and one study on non-alcoholic fatty liver disease (NAFLD) (Table 1) [12]. Other studies recruited a heterogeneous population of CLD patients of various etiologies without available individual data, and therefore were excluded from subgroup analysis. Seroconversion rate was 81% (95% CI, 76–86%) and 96% (95% CI, 93–97%) in CHB and NAFLD patients, respectively (Fig. 3).

Figure 3.

Pooled seroconversion rate in chronic liver disease according to etiology and cirrhosis status. CI, confidence interval; CHB, chronic hepatitis B; NAFLD, non-alcoholic fatty liver disease.

There were five studies on cirrhosis and six studies on non-cirrhosis CLD, four of which reported both outcomes. Seroconversion rate was 85% (95% CI, 75–91%) and 85% (95% CI, 78–90%) in patients with cirrhosis and those without cirrhosis, respectively (Fig. 3). Only one study reported seroconversion rate regarding cirrhosis severity (compensated cirrhosis: 78.9%; decompensated cirrhosis: 76.7%) [10].

Vaccine platform

There were four studies on inactivated vaccine and three on mRNA vaccine. Seroconversion rate was 86% (95% CI, 78–92%) and 89% (95% CI, 71–96%) in inactivated and mRNA vaccine, respectively (Supplementary Fig. 6).

Individual vaccine type

We used 80% as cut-off for classifying vaccine type of a study. There were two studies using BNT162b2 [11,15] and one using BBIBP-CorV [12] with 516 subjects. Other studies recruited a heterogeneous population of patients with various vaccine types without available individual data, and therefore were excluded from subgroup analysis. Seroconversion rate was 95% (95% CI, 72–99%) and 96% (95% CI, 93–97%) in BNT162b2 and BBIBP-CorV subgroups, respectively (Supplementary Fig. 7).

Region

There were four studies from the East and three from the West. Seroconversion rate was 86% (95% CI, 78–92%) and 89% (95% CI, 1–96%) in the East and West subgroups, respectively (Supplementary Fig. 8).

Cell-mediated vaccine immunogenicity

Only one study reported T-cell immune response among cirrhosis patients [15]. A T cell response was observed in 65% of cirrhosis patients, 37% of LT recipients and 100% of control subjects, with a strong response being present in 46%, 32%, and 100% in the three groups, respectively.

Adverse events

There were five studies (inactivated vaccine: 4; mRNA vaccine: 1) reporting adverse events with 1,360 subjects. Prevalence of adverse events was 27% (95% CI, 18–38%) with considerable heterogeneity (P<0.01; I²=88%) (Supplementary Fig. 9). Ai et al. [10] reported three subjects having grade 3 laboratory abnormalities with raised alanine transaminase five times above upper limit of normal, one of whom developed trend of acute liver failure requiring hospitalization (grade 4). Ruether et al. [15] reported two subjects with severe systemic side effects or requiring medications (grade 3) and one requiring hospitalization (grade 4). Supplementary Table 2 showed pooled prevalence of local and systemic adverse events among inactivated vaccine recipients. The most common local and systemic adverse event was pain (13%; 95% CI, 7–23%) and fatigue (3%; 95% CI, 2–5%), respectively. The study using mRNA vaccine did not report detailed data on individual adverse events.

Liver transplant recipients

Humoral immune response

There were 20 observational studies with 2,147 subjects. All studies were conducted in the West. Pooled seroconversion rate was 66% (95% CI, 58–73%) with considerable heterogeneity (P<0.01; I²=89%) (Fig. 4). The funnel plot appeared to be have some asymmetry (P=0.059 by Egger test), indicating publication bias (Supplementary Fig. 10). Trim and fill-method was used to adjust for publication bias, and the pooled seroconversion rate was 69% (95% CI, 61–76%).

Figure 4.

Pooled seroconversion rate in liver transplant recipients. CI, confidence interval.

Meta-regression analysis showed a trend for association between seroconversion of Nab and age (P=0.085) and method of antibody test (P=0.066 for CLIA vs. ECLIA) but not other factors (Supplementary Fig. 11).

Subgroup analysis

Method of antibody test

There were nine studies on CLIA, seven on ELISA, and four on ECLIA. Seroconversion rate was 71% (95% CI, 61–79%), 56% (95% CI, 43–69%), 70% (95% CI, 47–86%) in CLIA, ELISA and ECLIA, respectively (Supplementary Fig. 12).

Age

There were nine studies with median age ≥60 years and four studies with median age <60 years. A total of 1,826 subjects were included. Seroconversion rate was 64% (95% CI, 52–74%) and 77% (95% CI, 70–83%) in the older and younger age groups, respectively (Supplementary Fig. 13).

Individual vaccine type

All studies used mRNA vaccines (BNT162b2: 10; mRNA-1273: 4) with 1,640 subjects. We used 80% as cut-off for classifying vaccine type of a study. Seroconversion rate was 66% (95% CI, 55–75%) and 73% (95% CI, 63–81%) in BNT162b2 and mRNA-1273 subgroups, respectively (Fig. 5).

Figure 5.

Pooled seroconversion rate in liver transplant recipients according to individual vaccine type. CI, confidence interval.

Number of immunosuppressants

Four studies reported data on use of ≥2 immunosuppressants with 274 subjects. Seroconversion rate was 62% (95% CI, 43–79%) (Supplementary Fig. 14).

Cell-mediated vaccine immunogenicity

Four studies reported cell-mediated immune response in 157 LT recipients. T cell response rate was 65% (95% CI, 30–89%) with considerable heterogeneity (P<0.01; I²=90%) (Supplementary Fig. 15). Among those with negative humoral response in two studies, T cell response rate was 52% (95% CI, 12–90%) (Supplementary Fig. 15).

Adverse events

Three studies reported adverse events with 251 subjects. Pooled prevalence of adverse events was 63% (95% CI, 39–82%) with considerable heterogeneity (P<0.01; I²=92%) (Supplementary Fig. 16). Ruether et al. [15] reported 17 subjects with severe systemic side effects or requiring medications (grade 3) and one subject requiring hospitalization (grade 4). Data on individual adverse events were not reported in these studies.

Seroconversion rate among LT recipients receiving third dose

Three observational studies with 151 subjects were conducted in the West. Pooled seroconversion rate was 88% (95% CI, 58–98%) with considerable heterogeneity (P<0.01; I²=83%) (Supplementary Fig. 17).

DISCUSSION

This is the first meta-analysis to report COVID-19 vaccine immunogenicity and reactogenicity among CLD patients and LT recipients. Overall seroconversion rate ranges between 84% (based predominantly on Nab) and 91% (based predominantly on anti-spike antibody) among CLD patients; similar immunogenicity is noted regardless of cirrhosis status. Seroconversion rate of anti-spike antibody is 68% after two doses and 88% after third dose among LT recipients.

CLD

CLD patients are at a higher risk of developing severe COVID-19 disease and acute decompensation [31] with mortality reaching 14% [31,32]. Owing to immune dysregulation, CLD patients had lower immunologic response rate to inactivated vaccines like influenza or hepatitis vaccines [33]. CLD and fibrosis hamper production of innate immunity proteins and pattern recognition receptors, and adversely influence B- and Tlymphocytes in terms of absolute counts and functions via various mechanisms. However, the pooled seroconversion rate is good, ranging from 84% to 91% in our meta-analysis. Notably, although seroconversion rate is similar among CLD patients compared with healthy controls, their titer is generally lower [11,15]. A lower seroconversion rate of Nab of 77% was noted in the study by Ai et al. [10] recruiting subjects (87.8% CHB) who received inactivated vaccines. Another study of CHB patients receiving inactivated vaccines also found a seroconversion rate of Nab at 64.0–78.9%, dependent on HBV activity and cirrhosis status [26]. Our meta-analysis showed a numerical difference in seroconversion rate for CHB and NAFLD patients (81% vs. 96%). Nonetheless, a firm conclusion could not be drawn as there were only three studies on CHB (using three different inactivated vaccines) and one on NAFLD (using BBIBP-CorV only), and the difference could be due to different vaccine platforms used in each study. The seroconversion rate appears to be similar among younger and older subjects (85% vs. 88%).

There is also no difference in seroconversion rate between cirrhotic and non-cirrhotic groups (both 85%). There is only one study reporting no difference in vaccine immunogenicity as regards cirrhosis severity (compensated cirrhosis: 78.9%; decompensated cirrhosis: 76.7%) [10]. Subgroup analysis showed no difference in seroconversion rate between inactivated and mRNA vaccines.

Measuring anti-spike immunoglobulin G (IgG) or anti-RBD IgG results in a slightly higher seroconversion rate than Nab (91% vs. 84%). This difference is exemplified by one study showing seroconversion rate of 64.0–78.9% for Nab (dependent on HBV replication and cirrhosis status) and 96–100% for anti-spike IgG or anti-RBD IgG [26]. Nab level is a surrogate marker of vaccine effectiveness against symptomatic infection [22-24]. Anti-spike and anti-RBD IgG levels correlate with Nab [34] but not equate Nab. Using ECLIA to measure antibody level also results in slightly lower seroconversion rate compared with CLIA and ELISA (76% vs. 89% vs. 88%).

LT

Pooled seroconversion rate is less satisfactory (66%) among LT recipients, in particular for older than younger patients (64% vs. 77%). However, when compared with other organ transplant recipients (e.g., kidney, heart), LT recipients have higher seroconversion rate [19,35]. This may be related to stricter and higher levels of immunosuppression in other organ transplant recipients. However, all studies except one [35] reported seroconversion rate of anti-spike antibody but not Nab. Hall et al. [35] noted that 28.5% of organ transplant recipients with anti-RBD did not have Nab. Seroconversion rate of anti-spike IgG varied from 38% to 100%, likely related to variance in immunosuppression regimen. Known risk factors for seronegativity include high-dose steroid, triple immunosuppression, mycophenolate mofetil [20,36], low B-lymphocytes [15], hypogammaglobulinemia [36], vaccination during the first year post-transplantation [36], low estimated glomerular filtration rate [20], old age and alcohol-related liver disease [12]. Our meta-analysis showed that pooled seroconversion rate of patients receiving ≥2 immunosuppressants is slightly lower (62%) than that of whole cohort (66%). Subgroup analysis also shows the seroconversion rate of mRNA-1273 is slightly higher than that of BNT162b2 (73% vs. 66%). Importantly, pooled seroconversion rate increases to 88% after booster dose. Data on immunogenicity of inactivated vaccines in LT recipients are currently lacking. Notably, using ELISA to measure antibody level also results in slightly lower seroconversion rate compared with CLIA and ECLIA (56% vs. 71% vs. 70%).

There are four studies reporting T-cell immune response, with a pooled response rate of 65% [15,35-37]. Similar to the phenomenon observed in humoral response, level of T cell response is higher in LT recipients than other organ transplant recipients, e.g., heart transplant [36]. Our meta-analysis shows 52% have T-cell response despite seronegativity. Vaccine-induced T-cell response may offer protection via suppressing viral replication and supporting long-term memory of the immune system [38], hence protecting against severe infection despite seronegativity [23].

Concerning vaccine reactogenicity, pooled prevalence of adverse reactions is 27% among CLD patients receiving mainly inactivated vaccines, which is similar among healthy subjects (23% in a meta-analysis of randomized controlled trials) [39]. There is only one study reporting no significant difference in frequency of adverse events as regards cirrhosis status (non-cirrhosis: 15.5%; compensated cirrhosis: 16.3%; decompensated cirrhosis: 20.0%) [10]. As for LT recipients receiving mRNA vaccines, pooed prevalence of adverse reactions is 63%, compared with 48% among healthy subjects [39].

Our study findings support current international recommendation on COVID-19 vaccination in CLD patients and LT recipients [13,40]. LT recipients should receive vaccine platforms with more data (e.g., mRNA vaccine) and third-dose booster. Another strategy may be heterologous vaccination [41], in which seroconversion rate of 81.8% was reported for 8% of LT cohort who had heterologous vaccination in the study by Ruether et al. [15].

Limitations of the current study should be acknowledged. First, some studies did not measure Nab level, and the test kits differed among different studies. Second, the optimal antibody thresholds for protection is still unknown. Titers above the cut-off should protect against severe disease for the majority of vaccine recipients, but not against asymptomatic infection [23,42,43]. Third, only three studies reported vaccine immunogenicity among CHB patients and one on NAFLD; others recruited a heterogeneous population of CLD patients without available data for individual disease etiology (e.g., chronic viral hepatitis, NAFLD, autoimmune hepatitis) which may have different vaccine immunogenicity, in particular among autoimmune liver diseases which require immunosuppressants. Similarly, the LT recipients were comprised of a heterogeneous population of various disease etiology and different immunosuppressive regimen. Individual studies did not provide the seroconversion rate according to disease etiology and immunosuppressive regimen, and therefore subgroup analysis could not be performed according to these factors. Fourth, we did not include studies with general population that might enrol CLD recipients for comparison.

While an excellent safety profile is demonstrated in CLD and LT patients, the former group has good humoral response and the latter has lower response. Third-dose booster or heterologous vaccination may be considered in LT recipients, although more studies with larger sample size are warranted before this practice is widely recommended.

Notes

Authors’ contributions

Dr. Ka-Shing Cheung and Mr. Chiu Hang Mok were involved with study concept and design; acquisition of data; analysis and interpretation of data; drafting of manuscript; Mr. Xianhua Mao, Dr. Ricky Zhang and Prof. Ivan FN Hung were involved with analysis and interpretation of data; and critical revision of the manuscript for important intellectual content. Profs. Wai-Kay Seto and Man-Fung Yuen were involved with the study concept and design; analysis and interpretation of data; drafting of manuscript; critical revision of the manuscript for important intellectual content; and study supervision. The corresponding author had full access to all data, and was fully responsible for the data integrity and statistical analysis. All authors revised the manuscript and approved the final version of this article.

Conflicts of Interest

The authors have no conflicts to disclose.

Abbreviations

CHB

chronic hepatitis B

confidence interval

CLD

chronic liver disease

CLIA

chemiluminescence immunoassays

COVID-19

coronavirus disease 2019

ECLIA

electrochemiluminescence immunoassay analyzer

ELISA

enzyme-linked immunosorbent assay

IgG

immunoglobulin G

IQR

interquartile range

liver transplant

Nab

neutralising antibody

NAFLD

non-alcoholic fatty liver disease

NOS

Newcastle-Ottawa scale

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

RBD

receptor binding domain

SUPPLEMENTAL MATERIAL

Supplementary material is available at Clinical and Molecular Hepatology website (http://www.e-cmh.org).

Supplementary Figure 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. COVID-19, corona-virus disease 2019.

cmh-2022-0087-suppl1.pdf

Supplementary Figure 2.

Funnel plot of seropositivity in chronic liver disease.

cmh-2022-0087-suppl2.pdf

Supplementary Figure 3.

Meta-regression analysis for seropositivity in chronic liver disease. Bubble plot with fixed meta-regression line of (A) region, (B) participant number, (C) age ≥60, (D) etiology of liver disease, (E) cirrhosis status, (F) vaccine type, (G) vaccine platform, (H) antibody type, (I) time interval of antibody measurement from second dose of vaccination (≥30 days), (J) method of antibody test (ECLIA vs. ELISA), (K) method of antibody test (CLIA vs. ECLIA), (L) method of antibody test (CLIA vs. ELISA). The size of circles is proportional to weight of each study in fitted random effects meta-regression. ECLIA, electrochemiluminescence immunoassay analyzer; ELISA, enzyme-linked immunosorbent assay; CLIA, chemiluminescence immunoassays.

cmh-2022-0087-suppl3.pdf

Supplementary Figure 4.

Pooled seroconversion rate in chronic liver disease – subgroup by method of antibody test. CI, confidence interval; CLIA, chemiluminescence immunoassays; ELISA, enzyme-linked immunosorbent assay; ECLIA, electrochemiluminescence immunoassay analyzer.

cmh-2022-0087-suppl4.pdf

Supplementary Figure 5.

Pooled seroconversion rate in chronic liver disease – subgroup by age ≥60 years. CI, confidence interval.

cmh-2022-0087-suppl5.pdf

Supplementary Figure 6.

Pooled seroconversion rate in chronic liver disease – subgroup by vaccine platform. CI, confidence interval.

cmh-2022-0087-suppl6.pdf

Supplementary Figure 7.

Pooled seroconversion rate in chronic liver disease – subgroup by individual vaccine type. CI, confidence interval.

cmh-2022-0087-suppl7.pdf

Supplementary Figure 8.

Pooled seroconversion rate in chronic liver disease – subgroup by region. CI, confidence interval.

cmh-2022-0087-suppl8.pdf

Supplementary Figure 9.

Adverse events of vaccine in chronic liver disease patients. CI, confidence interval.

cmh-2022-0087-suppl9.pdf

Supplementary Figure 10.

Funnel plot of seroconversion rate in liver transplant recipients.

cmh-2022-0087-suppl10.pdf

Supplementary Figure 11.

Meta-regression analysis for seroconversion rate in liver transplant recipients. Bubble plot with fixed meta-regression line of (A) region (Europe vs. North America), (B) region (Europe vs. Israel), (C) region (Israel vs. North America), (D) participant number, (E) age ≥60, (F) vaccine type, (G) time interval of antibody measurement from second dose of vaccination (≥30 days), (H) method of antibody test (ECLIA vs. ELISA), (I) method of antibody test (CLIA vs. ECLIA), (J) method of antibody test (CLIA vs. ELISA). The size of circles is proportional to weight of each study in fitted random effects meta-regression. ECLIA, electrochemiluminescence immunoassay analyzer; ELISA, enzyme-linked immunosorbent assay; CLIA, chemiluminescence immunoassays.

cmh-2022-0087-suppl11.pdf

Supplementary Figure 12.

Pooled seroconversion rate in liver transplant recipients – subgroup by method of antibody test. CI, confidence interval; CLIA, chemiluminescence immunoassays; ELISA, enzyme-linked immunosorbent assay; ECLIA, electrochemiluminescence immunoassay analyzer.

cmh-2022-0087-suppl12.pdf

Supplementary Figure 13.

Pooled seroconversion rate in liver transplant recipients – subgroup by age ≥60 years. CI, confidence interval.

cmh-2022-0087-suppl13.pdf

Supplementary Figure 14.

Pooled seroconversion rate in liver transplant recipients– subgroup by 2 or more immunosuppressants. CI, confidence interval.

cmh-2022-0087-suppl14.pdf

Supplementary Figure 15.

Pooled cell-mediated vaccine immunogenicity in liver transplant recipients. CI, confidence interval.

cmh-2022-0087-suppl15.pdf

Supplementary Figure 16.

Adverse events of vaccine in liver transplant recipients. CI, confidence interval.

cmh-2022-0087-suppl16.pdf

Supplementary Figure 17.

Pooled seroconversion rate in liver transplant recipients with third dose of vaccine. CI, confidence interval.

cmh-2022-0087-suppl17.pdf

Supplementary Table 1.

Quality assessment according to Newcastle-Ottawa quality assessment scale

cmh-2022-0087-suppl18.pdf

Supplementary Table 2.

Background characteristics of the included studies for liver transplant recipients with third dose of vaccine

cmh-2022-0087-suppl19.pdf

Supplementary Referencescmh-2022-0087-suppl20.pdf

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Article information Continued

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Notes

Study Highlights

• Chronic liver disease patients, either cirrhotic or non-cirrhotic, have good humoral response to inactivated or mRNA COVID-19 vaccine

• Liver transplant recipients have lower humoral response to mRNA vaccine and hence early booster dose should be considered

• COVID-19 vaccine has good safety profile in both chronic liver disease patients and liver transplant recipients

Table 1.

Background characteristics of the included studies

Study		Country	Study duration	Participants	Age (years)	Male	Liver disease	Immunosup-pressants used	Vaccine type	Antibody type	Time interval of antibody measurement from second dose of vaccination	Method of antibody test	Cut-off of antibody level regarded as seropositive
Chronic liver disease
	Ai et al. [10]	China	January to August 2021	437	Median (IQR): 47.0 (38.0–56.0)	278 (63.6%)	Non-cirrhotic chronic liver disease: HBV, 260 (91.5%); HCV, 8 (2.82%); NAFLD, 9 (3.17%); ALD, 1 (0.35%); AIH/PBC/PSC, 1 (0.35%); others, 5 (1.76%)	NA	CoronaVac: NA	Neutralising Ab	≥14 days	CLIA	>10.0 AU/mL
									BBIBP-CorV: NA
							Cirrhosis: HBV, 124 (81.0%); HCV, 12 (7.84%); NAFLD. 3 (1.96%); AIH/PBC/PSC, 7 (4.58%); others, 7 (4.58%)		WIBP-CorV: NA
	Bakasis et al. [11]	Greece	March to May 2021	87	Median (range): cirrhosis, 67.0 (27–86); noncirrhotic liver disease, 65.0 (35–81)	43 (49.4%)	Non-cirrhotic chronic liver disease: HBV, 23 (46.9%); HCV, 1 (2.04%); NAFLD, 7 (14.3%); AIH, 6 (12.2%); PBC, 11 (22.4%); PSC, 1 (2.04%)	MTX: 5 (5.75%)	BNT162b2: 81 (93.1%)	Antispike Ab, neutralising Ab	Cirrhosis: 24 days (IQR, 14–57)	ELISA	Anti-spike Ab: >1.1 OD ratio
								AZA: 7 (8.05%)
								RTX: 4 (4.60%)
							Cirrhosis: HBV, 7 (18.4%); HCV, 1 (2.63%); NAFLD, 9 (23.7%); ALD, 6 (15.8%); AIH, 8 (21.1%); PBC, 1 (2.63%); PSC, 3 (7.89%); HSC, 1 (2.63%); BCS, 1 (2.63%); DILI, 1 (2.63%)	MMF: 6 (6.90%)	mRNA-1273: 6 (6.90%)		Non-cirrhotic liver disease: 25 days (IQR, 15–45)		Neutralising Ab: >30% inhibitory concentration
								TNFI: 4 (4.60%)
								S: 14 (16.1%)
	He et al. [26]	China	July to August 2021	362	Median (range): 45.0 (19.0–78.0)	223 (61.6%)	HBV, 362 (100%); cirrhosis, 48 (13.3%)	NA	CoronaVac: NA	Antispike Ab, antispike RBD Ab, neutralising Ab	≥21 days (range, 21–105)	ELISA	Anti-spike Ab, antispike RBD Ab: ≥2.1 OD ratio
	He et al. [26]	China	July to August 2021	362	Median (range): 45.0 (19.0–78.0)	223 (61.6%)	HBV, 362 (100%); cirrhosis, 48 (13.3%)	NA	BBIBP-CorV: NA	Antispike Ab, antispike RBD Ab, neutralising Ab	≥21 days (range, 21–105)	ELISA	Neutralising Ab: ≥20% inhibitory concentration
	Ruether et al. [15]	Germany	NA	48	Mean±SD: 53.8±9.5	108 (58.1%)	Cirrhosis: ALD, 23 (47.9%); VH, 3 (6.30%); AIH, 11 (22.9%); NAFLD, 4 (8.30%); CC, 5 (10.4%); ALF, 1 (2.10%); others, 1 (2.10%); HCC, 5 (10.4%)^*	NA	mRNA/mRNA: 44 (91.6%)	Antispike RBD Ab, antispike trimer Ab	Median (IQR): 28 days (21–41)	CLIA	Anti-spike RBD Ab: >100 U/mL
									BNT162b2: 38 (79.2%)			ECLIA	Anti-spike RBD Ab: >100 U/mL
									mRNA-1273: 6 (12.4%)				Anti-spike trimer Ab: >100 BAU/mL
									AZD1222/AZD1222: 1 (2.08%)
									AZD1222/mRNA: 3 (6.25%)
	Thuluvath et al. [21]	USA	NA	171	Mean±SD: noncirrhotic chronic liver disease, 60.4±13.9; liver cirrhosis, 63.8±11.1	Noncirrhotic chronic liver disease: 37 (40.2%)	Non-cirrhotic chronic liver disease: AIH/PBC/PSC, 36 (39.1%); ALD, 2 (2.17%); HBV/HCV, 20 (21.7%); NAFLD, 36 (39.1%); others, 8 (8.70%)	AZA: 25 (14.6%)	BNT162b2: 80 (46.8%)	Antispike Ab	Mean±SD: non-cirrhotic chronic liver disease, 40.8±19.6; liver cirrhosis, 40.9±23.9	ECLIA	>250 U/mL
						Noncirrhotic chronic liver disease: 37 (40.2%)		S: 19 (11.1%)	mRNA-1273: 77 (45.0%)
						Liver cirrhosis: 40 (50.6%)	Cirrhosis: AIH/PBC/PSC, 17 (21.5%); ALD, 17 (21.5%); HBV/HCV, 17 (21.5%); NAFLD, 33 (41.8%); others, 8 (10.1%)	TAC: 0 (0.00%)	mRNA-1273: 77 (45.0%)
						Liver cirrhosis: 40 (50.6%)		Others: 11 (6.43%)	JNJ-78436735: 14 (8.19%)
	Wang et al. [12]	China	October 2020 to March 2021	381	Median (IQR): 39.0 (33.0–48.0)	179 (47.0%)	NAFLD: 381 (100%)	NA	BBIBPCorV: 381 (100%)	Neutralising Ab	14 days	CLIA	NA
	Xiang et al. [25]	China	March to September 2021	149	Median (IQR): 41.0 (33.0–49.0)	108 (72.5%)	HBV: 284 (100%)	NA	CoronaVac: NA	Antispike RBD Ab, neutralising Ab	Median (IQR): 33 days (24–48)	CLIA	Anti-spike RBD Ab: 1 AU/mL
									BBIBP-CorV: NA				Anti-spike RBD Ab: 1 AU/mL
									WIBP-CorV: NA				Neutralising Ab: 0.05 AU/mL
Liver transplant
	Rashidi-Alavijeh et al. [44]	Germany	February to March 2021	43	Median (IQR): 47.0 (36.0–54.0)	26 (60.5%)	HCC: 10 (23.3%); PSC: 7 (16.3%); AC: 6 (14.0%); HCV: 3 (6.98%); ALF: 3 (6.98%); WD: 3 (6.98%); CC: 2 (4.65%); AAD: 2 (4.65%); others: 7 (16.3%)	TAC+EVE: 22 (51.2%)	BNT162b2: 43 (100%)	Antispike Ab	15 days (IQR: 12–24)	CLIA	≥13.0 AU/mL
								TAC+MMF: 11 (25.6%)
								TAC: 7 (16.3%)
								CSA: 2 (4.65%)
								EVE: 1 (2.33%)
	Boyarsky et al. [45]	USA	December 2020 to March 2021	129	NA	NA	NA	NA	BNT162b2: NA	Antispike Ab	Median (IQR): 29 days (28–31)	ECLIA	≥0.8 U/mL
	Boyarsky et al. [45]	USA	December 2020 to March 2021	129	NA	NA	NA	NA	mRNA-1273: NA	Antispike Ab	Median (IQR): 29 days (28–31)	ECLIA	≥0.8 U/mL
	Cholankeril et al. [16]	USA	January to February 2021	69	Median (IQR): 63.0 (51–68)	48 (69.6%)	ALD: 24 (34.8%); NAFLD: 13 (18.8%); HCC: 21 (30.4%)	TAC: 64 (92.8%)	BNT162b2: 69 (100%)	Antispike Ab	30–75 days	ELISA	Titer ≥1
								MMF: 23 (33.3%)
								S: 22 (31.9%)
	Davidov et al. [46]	Israel	January to May 2021	76	Mean±SD: 59.0±15	43 (56.6%)	HBV: 7 (9.30%); HCV: 19 (25.3%); NAFLD: 13 (17.3%); PSC: 11 (14.7%); PBC: 3 (4.00%); others: 23 (30.3%)	CNI (TAC/CSA): 40 (52.6%)	BNT162b2: 76 (100%)	Antispike RBD Ab	Mean±SD: 38±24 days	ELISA	Titer ≥1.1
								CNI+MMF: 12 (15.8%)
								CNI+EVE: 10 (13.2%)
								CNI+S: 9 (11.8%)
								CNI+MMF+S: 4 (5.26%)
								SRL: 1 (1.32%)
	Erol et al. [47]	Turkey	April to June 2021	10	NA	NA	NA	NA	BNT162b2: 4 (40.0%)	Antispike Ab	28–42 days	CLIA	≥50 AU/mL
	Erol et al. [47]	Turkey	April to June 2021	10	NA	NA	NA	NA	CoronaVac: 6 (60.0%)	Antispike Ab	28–42 days	CLIA	≥50 AU/mL
	Fernández-Ruiz et al. [37]	Spain	April to June 2021	13	NA	NA	NA	NA	mRNA-1273: 13 (100%)	Antispike Ab	14 days	ELISA	OD ≥1.1
	Guarino et al. [48]	Italy	May to August 2021	444	Median (IQR): seronegative, 65.6 (59.4-71.0); seropositive, 65.2 (56.9-70.1)	332 (74.8%)	VH: 342 (77.0%); ALD: 34 (7.66%); NAFLD: 8 (1.80%); AIH: 18 (4.05%); others: 43 (9.68%)	TAC/CSA: 357 (80.4%)	BNT162b2: 444 (100%)	Antispike Ab	Median (IQR): 1st collection, 28 days (28–31); 2nd collection, 88 days (86–91)	CLIA	>25 AU/mL
								MMF: 151 (34.0%)
								EVE/SRL: 118 (26.6%)
	Hall et al. [35]	Canada	March to April 2021	11	NA	NA	NA	NA	mRNA-1273: 11 (100%)	Antispike RBD Ab, neutralising Ab	28–42 days	ECLIA	Anti-spike RBD Ab: ≥0.8 U/mL
	Hall et al. [35]	Canada	March to April 2021	11	NA	NA	NA	NA	mRNA-1273: 11 (100%)	Antispike RBD Ab, neutralising Ab	28–42 days	ELISA	Neutralising Ab: >30% inhibitory concentration
	Herrera et al. [36]	Spain	NA	58	Median (range): 61.5 (18.0–88.0)	40 (69.0%)	NA	CNI: 53 (91.4%)	mRNA-1273: 58 (100%)	Antispike RBD Ab	≥28 days	CLIA	NA
								MMF: 15 (25.9%)
								S: 13 (22.4%)
								mTORI: 13 (22.4%)
	Holden et al. [17]	Denmark	From January 2021	13	NA	NA	NA	NA	BNT162b2: NA	Antispike Ab	Median (IQR): 5.6 weeks (5.1–6.3)	ELISA	Titer ≥1.1
	Huang et al. [18]	USA	January to April 2021	87	NA	NA	NA	NA	BNT162b2: NA	Antispike Ab	≥14 days	ELISA	Titer >1:50
	Huang et al. [18]	USA	January to April 2021	87	NA	NA	NA	NA	mRNA-1273: NA	Antispike Ab	≥14 days	ELISA	Titer >1:50
	Marion et al. [19]	France	January to April 2021	58	NA	NA	NA	NA	BNT162b2: NA	Antispike Ab	28 days	ELISA	NA
	Marion et al. [19]	France	January to April 2021	58	NA	NA	NA	NA	mRNA-1273: NA	Antispike Ab	28 days	ELISA	NA
	Mazzola et al. [49]	France	January to April 2021	58	Median (IQR): 64.0 (58.0–68.2)	43 (74.1%)	NA	S: 15 (25.9%)	BNT162b2: 58 (100%)	Antispike Ab	28 days	CLIA	≥50 AU/mL
								CNI: 45 (77.6%)
								MMF: 33 (56.9%)
								mTORI: 13 (22.4%)
	Mulder et al. [50]	Netherlands	March to July 2021	476	Median (IQR): BNT162b2, 71.0 (59.0–79.0); mRNA-1273, 59.0 (49.0–66.0); AZD1222, 63.0 (60.0–64.0)	286 (60.1%)	PSC: 101 (21.2%); HCC: 103 (21.6%); ALF: 46 (9.66%); PBC/SSC/CBD: 37 (7.77%); NAFLD/ALD: 42 (8.82%); CC: 22 (4.62%); VH: 24 (5.04%); DC: 20 (4.20%); others: 50 (10.5%); retransplant: 31 (6.51%)	TAC: 243 (51.1%)	BNT162b2: 25 (5.25%)	Antispike Ab	Median (IQR): BNT162b2, 31 (29.0–40.0); mRNA-1273, 43.0 (33.0–56.3); AZD1222, 31.0 (26.0–38.0)	CLIA	NA
								MMF: 27 (5.67%)	BNT162b2: 25 (5.25%)
								CSA: 5 (1.05%)	mRNA-1273: 430 (90.3%)
								SRL: 2 (0.42%)	mRNA-1273: 430 (90.3%)
								EVE: 1 (0.21%)	AZD1222: 21 (4.41%)
								AZA: 1 (0.21%)
								S: 39 (8.19%)
								TAC+MMF: 113 (23.7%)
								TAC+S: 27 (5.67%)
								TAC+SRL: 16 (3.36%)
								CSA+EVE: 6 (1.26%)
								TAC+AZA: 7 (1.46%)
								TAC+EVE: 5 (1.05%)
								MMF+EVE: 3 (0.63%)
								MMF+SRL: 2 (0.42%)
								AZA+S: 1 (0.21%)
								CSA+AZA: 1 (0.21%)
								MMF+S: 1 (0.21%)
								TAC+MMF+S: 8 (1.68%)
								TAC+SRL+S: 1 (0.21%)
	Nazaruk et al. [51]	Poland	January to June 2021	55	Mean±SD: 58.4±13.3	44 (80.0%)	NA	S: 20 (36.4%)	BNT162b2: 55 (100%)	Antispike Ab	28–56 days	CLIA	>50 AU/mL
								MMF: 16 (29.1%)
								AZA: 5 (9.10%)
								CSA: 11 (20.0%)
								TAC: 43 (78.2%)
								SRL: 2 (3.60%)
								EVR: 2 (3.60%)
								CNI/MMF: 24 (43.6%)
								CNI+S/MMF/AZA/mTORI: 18 (32.7%)
								CNI/mTORI+S+MMF/AZA: 13 (23.6%)
	Rabinowich et al. [20]	Israel	From December 2020	80	Mean±SD: 60.1±13.3	56 (70.0%)	HBV: 13 (16.3%); HCV: 26 (32.5%); NAFLD: 16 (20.0%); ALD: 3 (3.75%); AIH: 6 (7.50%); PBC: 3 (3.75%); PSC: 7 (8.75%); ALF: 2 (2.50%); CC: 3 (3.75%); WD: 1 (1.25%); SSC: 1 (1.25%); CHF: 1 (1.25%); HCC: 26 (32.5%)^*	S: 24 (30.0%)	BNT162b2: 80 (100%)	Antispike Ab	10–20 days	CLIA	≥15 AU/mL
								TAC: 65 (81.3%)
								CSA: 10 (12.5%)
								EVE: 18 (22.5%)
								AZA: 4 (5.00%)
								MMF: 40 (50.0%)
	Ruether et al. [15]	Germany	NA	138	Mean±SD: 55.0±13.2	79 (57.2%)	ALD: 28 (20.3%); VH: 17 (12.3%); AIH: 40 (29.0%); NAFLD: 7 (5.10%); PLD: 5 (3.60%); CC: 13 (9.4%); ALF: 5 (3.60%); others: 23 (16.7%); HCC: 25 (18.1%)^*	S: 43 (31.2%)	mRNA/mRNA: 121 (87.7%)	Antispike RBD Ab, antispike trimer Ab	Median (IQR): 29 days (25–39)	CLIA	Anti-spike RBD Ab: >100 U/mL
								TAC: 95 (68.8%)	mRNA/mRNA: 121 (87.7%)			ECLIA	Anti-spike RBD Ab: >100 U/mL
								CSA: 33 (23.9%)	BNT162b2: 110 (79.7%)				Anti-spike trimer Ab: >100 BAU/mL
								CNI: 33 (23.9%)	BNT162b2: 110 (79.7%)
								CNI+S: 19 (13.8%)	mRNA-1273: 11 (7.97%)
								CNI+mTORI: 17 (12.3%)	mRNA-1273: 11 (7.97%)
								CNI+MMF: 48 (34.8%)	AZD1222/AZD1222: 6 (4.35%)
								CNI+AZA: 9 (6.50%)	AZD1222/AZD1222: 6 (4.35%)
								Biologics: 8 (5.8%)	AZD1222/mRNA: 11 (7.97%)
	Strauss et al. [52]	USA	January to April 2021	161	Median (IQR): 64.0 (48.0–69.0)	69 (42.9%)	NA	TAC: 81 (50.3%)	BNT162b2: 85 (52.8%)	Antispike Ab, antispike RBD Ab	Median (IQR): 30 days (28–31)	ECLIA	>250 U/mL
								MMF: 35 (21.7%)	BNT162b2: 85 (52.8%)
								S: 22 (13.7%)	mRNA-1273: 76 (47.2%)
								SRL: 11 (6.83%)
								CSA: 8 (4.97%)
								AZA: 6 (3.73%)
								ERL: 3 (1.86%)
	Thuluvath et al. [21]	USA	NA	62	Mean±SD: 65.7±8.7	41 (66.1%)	AIH/PBC/PSC: 8 (12.9%); ALD: 13 (21.0%); HBV/HCV: 26 (41.9%); NAFLD: 15 (24.2%); others: 16 (25.8%)	AZA: 2 (3.23%)	BNT162b2: 24 (38.7%)	Antispike Ab	Mean±SD: 38.9±19.6 days	ECLIA	>250 U/mL
								S: 8 (12.9%)	BNT162b2: 24 (38.7%)
								TAC: 41 (66.1%)	mRNA-1273: 33 (53.2%)
								Others: 29 (46.8%)	JNJ-78436735: 5 (8.06%)
	Timmermann et al. [53]	Germany	May to July 2021	118	Mean (range): 66.1 (28.0–89.0)	75 (63.6%)	ALD: 25 (21.1%); VH: 28 (23.7%); LT: 26 (22.0%); AIH: 18 (15.3%); CC: 4 (3.4%); other: 17 (14.4%)	TAC: 42 (35.6%)	BNT162b2: 114 (96.6%)	Antispike Ab	Mean (range): 44.6 days (21–132)	ELISA	NA
								MMF: 16 (13.6%)	BNT162b2: 114 (96.6%)
								TAC+MMF: 24 (20.3%)	mRNA-1273: 3 (2.54%)
								TAC+EVE: 15 (12.7%)	mRNA-1273: 3 (2.54%)
								EVR: 1 (0.85%)	JNJ-78436735: 1 (0.85%)
								CSA+MMF: 3 (2.54%)
								CSA: 2 (1.69%)
								TAC+AZA: 1 (0.85%)

IQR, interquartile range; HBV, hepatitis B virus; HCV, hepatitis C virus; NAFLD, non-alcoholic fatty liver disease; ALD, alcoholic liver disease; AIH, autoimmune hepatitis; PBC, primary biliary cholangitis; PSC, primary sclerosing cholangitis; NA, not available; Ab, anti-body; CLIA, chemiluminescence immunoassays; HSC, hepatic sarcoidosis; BCS, Budd-Chiari syndrome; DILI, drug induced liver injury; MTX, methotrexate; AZA, azathioprine; RTX, rituximab; MMF, mycophenolate mofetil; TNFI, tumour necrosis factor inhibitor; S, steroid; OD, optical density; RBD, receptor binding domain; ELISA, enzyme-linked immunosorbent assay; SD, standard deviation; VH, viral hepatitis; CC, cryptogenic cirrhosis; ALF, acute liver failure; HCC, hepatocellular carcinoma; ECLIA, electrochemiluminescence immunoassay analyzer; TAC, tacrolimus; AC, alcoholic cirrhosis; WD, Wilson’s disease; AAD, α-1 antitrypsin deficiency; EVE, everolimus; CSA, cyclosporin A; CNI, calcineurin inhibitors; SRL, sirolimus; mTORI, mTOR inhibitors; SSC, secondary sclerosing cholangitis; CBD, congenital biliary disease; DC, dysmetabolic cirrhosis; CHF, congenital hepatic fibrosis; PLD, pediatric liver disease; LT, liver tumour.

Concomitant condition.