Next Article in Journal
Influenza Vaccine Utilization: A Comparison between Urban and Rural Counties in Florida
Next Article in Special Issue
Influence of a Heterologous (ChAdOx1-nCoV-19/BNT162b2) or Homologous (BNT162b2/BNT162b2) Vaccination Regimen on the Antibody and T Cell Response to a Third Vaccination with BNT162b2
Previous Article in Journal
Comparison of High-Performance Liquid Chromatography with Sucrose Density Gradient Ultracentrifugation for the Quantification of Foot-and-Mouth Disease Vaccine Antigens
Previous Article in Special Issue
Cross-Reactivity between Half Doses of Pfizer and AstraZeneca Vaccines—A Preliminary Study
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Booster COVID-19 Vaccines for Immune-Mediated Inflammatory Disease Patients: A Systematic Review and Meta-Analysis of Efficacy and Safety

by
Ainsley Ryan Yan Bin Lee
1,
Shi Yin Wong
1 and
Sen Hee Tay
2,3,*
1
Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
2
Division of Rheumatology, Department of Medicine, National University Hospital, Singapore 119228, Singapore
3
Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
*
Author to whom correspondence should be addressed.
Submission received: 12 March 2022 / Revised: 17 April 2022 / Accepted: 18 April 2022 / Published: 22 April 2022
(This article belongs to the Special Issue Effectiveness, Safety and Immunogenicity of SARS-CoV-2 Vaccines)

Abstract

:
Background: Seroconversion and longevity of vaccine-induced immune response is blunted in immune-mediated inflammatory disease (IMID) patients owing to immunosuppressive regimens. COVID-19 booster vaccines after a primary series have been proposed with inconclusive evidence on efficacy to date. Methods: This PROSPERO-registered systematic review (CRD42022302534) was conducted according to PRISMA guidelines. PubMed, EMBASE, CENTRAL, Web of Science, CORD-19, WHO ICTRP, and medRxiv were searched up to 28 February 2022 for eligible studies. Risk of bias was assessed using the Joanna Briggs Institute critical appraisal tools. Results: From 6647 records, 17 prospective studies were included for systematic review and 12 in meta-analysis of primary series non-responders. The risk of bias was low. Pooling 340 non-responders, a booster dose proved effective with 0.47 seroconverting (95% CI: 0.32–0.63, I2 = 82%). Rituximab therapy was associated with significant impairment, with risks of 0.25 (95% CI: 0.17–0.36, I2 = 50.7%) versus 0.81 (95% CI: 0.72–0.87, I2 = 0.0%) for those without rituximab therapy. A systematic review of antibody levels against COVID-19 showed several-fold increases across studies. Incidence of local and systemic adverse events, including disease flares, were either comparable or slightly increased after the booster dose compared to primary series. No major events such as myocarditis or death were reported. Conclusion: Our results show that booster doses are effective in eliciting seroconversion in non-responders, bolstering immunity to COVID-19. It has also not been associated with major adverse events.

1. Introduction

Since the declaration of COVID-19 as a pandemic of global health concern, patients with immune-mediated inflammatory diseases (IMID) have been studied as a vulnerable population with increased risks of severe infection and mortality, owing to the plethora of immunosuppressive medications IMID patients are often receiving [1,2]. Vaccinations have widely been recommended for IMID patients to afford protection against clinically-significant disease [3]. Vaccine-mediated immune responses may be blunted due to the suppressed immune system of IMID patients [4]. Furthermore, for those who seroconvert, the antibody response may be shorter lived [5].
The range of immunosuppressive medications commonly used in IMID patients can broadly be divided into conventional synthetic biologic disease-modifying anti-rheumatic drugs (DMARDs), biologic DMARDs, and targeted synthetic DMARDs with diverse effects and mechanisms leading to immunosuppression [6,7]. Therapies that result in the depletion of B cells have long been hypothesised to impair immunogenicity to vaccines, though this has been demonstrated to be significant with rituximab [8,9] and ocrelizumab [10] but not belimumab [11]. A recent systematic review demonstrated that various DMARDs, including methotrexate, mycophenolate, and Janus kinase inhibitors, impair immune responses to vaccines [12]. It is also of concern that IMID patients, owing to the systemic immune response evoked by vaccines, may lead to disease flares [13].
In previous work, it was found that seroconversion rates are depressed amongst immunocompromised patients, including IMIDs patients, following the first and second doses of COVID-19 vaccines [14,15]. This further suggests the importance of exploring additional measures such as the administration of a booster dose. To date, there have been no systematic reviews looking at the efficacy of COVID-19 vaccines booster doses in IMID patients. As institutions such as the American College of Rheumatology have moved to recommend COVID-19 booster vaccination in patients on immunomodulatory drugs, a systematic review is warranted to evaluate its efficacy and safety in IMID patients [16]. This review aims to study seroconversion rates and antibody levels post-vaccination in IMID patients. Furthermore, we seek to ascertain patient and treatment factors associated with response to booster doses in IMID patients.

2. Materials and Methods

2.1. Search Strategy

The systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [17] and registered on PROSPERO at CRD42022302534.
Searches of the databases MEDLINE (via PubMed), EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, World Health Organisation International Clinical Trials Registry Platform, COVID-19 Open Research Dataset, and medRxiv were searched for articles published from 1 January 2021 to 28 February 2022. There was no restriction on the language of publication. The search strategy is detailed in Table S1. Additional searching of references of all included studies was performed.

2.2. Selection of Articles

All studies including at least five IMID patients receiving a booster dose of a COVID-19 vaccine were considered for inclusion by two researchers (A.R.Y.B.L. and S.Y.W.) with any differing opinions resolved by consultation of a third researcher (S.H.T.). Duplicates were removed using Endnote X20. A booster dose of COVID-19 vaccine was considered to be any COVID-19 vaccine after completion of a primary series of vaccination, one dose of Ad26.COV2.S or two doses of mRNA-1273, BNT162b2, AZD1222, or NVX-CoV2373. Observational studies and interventional studies were included. Single case reports or case series with fewer than five patients were excluded. Patients had to be diagnosed with IMIDs, such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), inflammatory bowel diseases (IBD), multiple sclerosis (MS), and other diseases as defined by Kuek et al. [18].
The primary outcome of interest was the proportion of IMID patients that were tested to be seronegative after completing a primary series of COVID-19 vaccination but became seropositive after a booster dose. Seroconversion status should be determined according to a validated threshold, such as determined by the manufacturer of the assay used, which will be extracted and reported. The secondary outcome of interest was the mean or median proportion of rise in serological titre of IMID patients before and after receiving a booster dose.
Studies not adhering to the aforementioned inclusion criteria were excluded. Additionally, studies were excluded if they reported seroconversion data in a form from which the proportions, risk of seroconversion, or number of seroconverted participants could not be derived and could not be obtained after consultation of the corresponding authors.

2.3. Extraction of Data

Data were extracted according to a pre-determined proforma in Microsoft Excel version 16.45 by one researcher (A.R.Y.B.L.), with all key extracted data reviewed and quality-checked at the end of the data-extraction phase by the same researcher.
The study characteristics comprised of setting, primary and secondary outcomes, study design, sample size, dropout and non-response rates, and inclusion and exclusion criteria. The participant data collected comprised of age, sex, and comprehensive disease and treatment history, including immunosuppressive regimen. Intervention-related data included vaccine type and brand, number receiving each vaccine, and median or mean interval between doses. Outcome-related data comprised of assay, antibody measured, and method of measurement.

2.4. Risk of Bias Assessment

The methodological quality and risk of bias of the studies were assessed using the Joanna Briggs Institute (JBI) critical appraisal checklist [19]. JBI tool for case series, cohort studies and randomised-controlled studies were used to assess the studies which described the response to vaccines in patients with IMIDs [20]. Risk of bias for each study was assessed independently by two researchers (A.R.Y.B.L. and S.Y.W.) with any differing opinions resolved by consensus.

2.5. Analysis of Data

The generalised linear mixed effects model was used to pool the logit transformed proportions of IMID patients who achieved seroconversion after a booster dose. We assessed for and considered between-study heterogeneity as significant if the p-value of the Q-test was <0.10 or if the I statistic was ≥50%. Subgroup analyses were performed to see if seroconversion was influenced by age, booster vaccine administered, disease, and anti-CD20 treatment and compared with tests for subgroup differences. All analyses were conducted using R (version 4.1.0) using the meta and metafor packages and considering a two-sided p value of <0.05 as statistically significant. Influence analysis was further conducted using the leave-one-out method and assessment for outliers. If any studies at a high risk of bias were identified, sensitivity analysis will be performed excluding these studies.
Publication bias was assessed via visual inspection of the funnel plot for asymmetry as well as quantitatively using Egger’s test. Sensitivity analysis was conducted using the trim-and-fill method after imputing potentially missing studies.

3. Results

From a total of 6647 records, a total of 17 prospective studies were included in this systematic review. The screening process is illustrated in the PRISMA flowchart in Figure 1. Of these studies, there were 12 observational studies [21,22,23,24,25,26,27,28,29,30,31,32], one randomised-controlled trial [33], and four case series [34,35,36,37]. The key trial characteristics of each included study are reported in Table 1, with a comparison of the characteristics of the studies included in the meta-analysis in Table S2.
COVID-19 booster vaccines administered in the studies included mRNA (Pfizer-BioNTech, BNT162b2 and Moderna, mRNA-1273) [21,22,23,24,25,26,27,28,29,30,34,35,36,37], non-replicating viral vector (AstraZeneca, AZD1222 and Janssen, Ad26.COV2.S) [21,28,29,30,34,35,36,37], protein subunit (Novavax, NVX-CoV2373) [33] and inactivated (Sinovac, CoronaVac) vaccines [35]. Bonelli et al. involved two cohorts receiving mRNA vaccines as the primary series, but one received heterologous AstraZeneca booster doses while the other received homologous mRNA boosters [29].
Most studies involved patients with diverse IMIDs. Schmiedeberg et al. [22] and Jyssum et al. [24] included only patients with RA while Felten et al. [36] included mostly RA patients and one patient with stiff-person syndrome. Schell et al. [23] included only IBD patients, and Kant et al. [37] and Speer et al. [25] only antineutrophil cytoplasmic antibody (ANCA) vasculitis patients. Achtnichts et al. [30] included patients with only MS.

3.1. Risk of Bias Assessment

Risk of bias assessment of all included studies was performed using the JBI critical appraisal checklists as presented in Tables S3–S5. Overall, no significant risk of bias was found.

3.2. Seroconversion in Non-Responders Elicited Following Booster Dose

A total of 12 studies reporting seroconversion rates in non-responders to a primary series of COVID-19 vaccination were included for meta-analysis, pooling a total of 340 non-responders after the primary series (Figure 2). The overall seroconversion risk is 0.47 (95% CI: 0.32–0.63) with the random-effects model. The overall heterogeneity was notable (I2 = 82%) thus showing that while booster doses could elicit seroconversion, especially-vulnerable subgroups who respond poorer would require further attention.
We undertook further subgroup analyses per protocol according to key disease and treatment factors (Table 2). Subgrouping by patients who were on anti-CD20 therapies (rituximab or ocrelizumab) versus patients on non-anti-CD20 therapies yielded significant subgroup differences (p-value < 0.0001). Patients on anti-CD20 therapy showed markedly-depressed seroconversion rates of 0.25 (95% CI: 0.17–0.36) compared to those without, exhibiting a seroconversion rate of 0.81 (95% CI: 0.72–0.87). Most heterogeneity was eliminated amongst each subgroup with non-anti-CD20 patients (I2 = 0.0%) while those on anti-CD20s showed reduced heterogeneity (I2 = 50.7%).
Furthermore, Simon et al. [21] and Speer et al. [25] each studied separate cohorts of patients with and without anti-CD20 therapies. From these, drastically poorer responses could be observed in the anti-CD20 cohorts with 6 of 33 (18.2%) and 0 of 8 (0.0%) of anti-CD20 patients, respectively, studied by Simon et al. and Speer et al. seroconverting after the booster dose, compared to 26 of 33 (78.8%) and 12 of 13 (92.3%) patients without anti-CD20 therapy.
We further performed subgroup analysis according to the underlying IMIDs. The subgroup effect was significant (p-value = 0.0286). As many studies included a mixed of IMIDs, this subgroup analysis was limited. In regard to the increasing risk of seroconversion, the cohort including only MS patients had the lowest risk of 0.06 (95% CI: 0.01–0.34), followed by RA including 76 patients from three cohorts with a pooled risk of 0.51 (95% CI: 0.12–0.89), ANCA vasculitis including 36 patients from two cohorts with a pooled risk of 0.53 (95% CI: 0.37–0.68). The subgroup for SLE consisted of eight patients who all seroconverted, leading to a subgroup risk with random effects of 0.94 (95% CI: 0.50–1.00). It is worth noting that the SLE patients studied by Assawasaksakul et al. [35] were not on anti-CD20 therapy, which may have contributed to the higher response rate, rather than the IMID itself. In contrast, the 16 MS patients studied by Achtnichts et al. [30] were all on anti-CD20 therapies, ocrelizumab or rituximab. Significant heterogeneity was noted in all subgroups except for ANCA vasculitis.
Subgroup analysis by vaccine type was conducted by pooling cohorts which received only one type of COVID-19 vaccine as a booster (test of subgroup differences, p-value = 0.0049). Cohorts which included only mRNA boosters had a seroconversion rate of 0.34 (95% CI: 0.16–0.58), higher than viral vector boosters with 0.22 (95% CI: 0.10–0.41). A significant number of cohorts received a mix of mRNA and non-mRNA vaccines, making it difficult in the current analysis to isolate the effect of vaccine type on seroconversion. Subgroup analysis by age did not demonstrate significant differences (p-value = 0.0571).

3.3. Rise in Antibody Levels after Booster Dose

As we anticipated there to be significant heterogeneity in the measurement and reporting of antibody levels, such as in the assay used and specific antibody measured, a systematic review without a meta-analysis approach was used to qualitatively assess antibody levels reported in Table 3.
Across all studies, booster doses resulted in a significant rise in antibody level. This ranged from an increase of 2.19-fold [23] to over 6250-fold [34]. In the study by Connolly et al., the median antibody level measured by the Roche Elecsys anti-RBD pan-Ig rose from less than 0.4 U/mL to over 2500 U/mL.

3.4. Increased Seroprotection against COVID-19 Variants of Significance

Mallory et al. [33] performed assays against COVID-19 variants of significance, Alpha, Beta, Delta and Omicron before and after the booster dose. A functional hACE2 receptor binding inhibition assay was performed before and after the booster dose, demonstrating respective rises in inhibition of 54.4-fold (ancestral), 21.9-fold (Alpha), 24.5-fold (Beta), 24.4-fold (Delta), and 20.1-fold (Omicron). Additionally, anti-rS IgG activity assays performed demonstrated marked rises in antibody response against all variants of significance.
Rituximab therapy appeared to be the most notable factor impairing the ability of IMID patients to mount an immune response against variants such as Delta. Speer et al. [25] found that the booster dose elicited Delta-neutralising activity in 12 of 13 (92%) without rituximab therapy. None of the eight patients on rituximab therapy demonstrated this.
Hadjadj et al. [27] studied the rise in neutralising antibodies against Alpha and Delta variants and found that neutralising activity increased in patients receiving methotrexate and other immunosuppressive drugs including steroids, csDMARDs, and biologics, except for rituximab. The cohort receiving rituximab did not exhibit increased neutralising activity against Alpha and Delta variants after the booster dose. Jyssum et al. [24] similarly found that rituximab-receiving patients did not exhibit significant seroconversion after the booster dose, but all had induced CD4 and CD8 T-cell responses to the Delta variant.

3.5. Reactogenicity and Adverse Events after the Booster Dose

Local and systemic adverse events following the booster dose was sought from each study. Furthermore, the incidence and severity of adverse events after the booster were compared to that after the first and/or second vaccine dose if reported by the authors. The largest study, including 211 IMID patients, by Dreyer-Alster et al. [32], reported 115 (54.5%) experiencing an adverse event, with fever/chills, fatigue, and injection site pain being the most common at 52 (24.6%), 50 (23.7%), and 46 (21.8%) occurrences, respectively. Importantly, seven patients (3.3%) reported an acute relapse of MS occurring a median (range) of 34 (14–67) days after receiving the booster dose.
Jyssum et al. [24] noted that the frequency of adverse events was comparable in IMID patients after the second (32 of 67, 48%) and booster (19 of 45, 42%) dose of mRNA vaccines. The frequency of specific adverse events was comparable after the second and booster doses, except for bleeding and bruises which were more frequent after the booster than the second dose. While disease flares were observed, they were rare and comparable in incidence to the primary vaccination series. Among patients who received a booster dose, 5 of 37 (14%), 3 of 39 (8%), and 7 of 45 (16%) reported IMID flares after the first, second, and booster doses, respectively.
Mallory et al. similarly found no major systemic adverse events after the booster dose of NVX-CoV2373, although the frequency of adverse events was higher after the booster dose (13.4% grade 3 and above) than primary series vaccinations (5.2% grade 3 and above). Two grade 4 local adverse events, pain and tenderness, were reported by one patient receiving a booster dose, while none did after the primary series. The case series by Schmiedeberg et al. [22] and Assawasaksakul et al. [35] similarly only reported transient local adverse events such as pain and systemic adverse events such as fatigue and fever.
While no serious adverse events such myocarditis or death were reported, it should be keenly noted that the sample populations receiving booster doses studied in this review are generally small.

3.6. Publication Bias, Influence and Sensitivity Analysis

Publication bias was not suggested when assessed visually using a trim-and-fill funnel plot (Figure S1) and quantitatively with Egger’s test (Figure S2). Leave-one-out analysis (Figure S3) and repeating analysis with either the fixed effects model (Figure S4) or random effects model with Hartung–Knapp adjustment (Figure S5) did not show significant changes in the overall results. Only two studies by Schmiedeberg et al. [22] and Jyssum et al. [24] were identified as outliers (Figure S6).

4. Discussion

4.1. Efficacy, Necessity, and Safety of a Booster Dose

Our systematic review and meta-analysis has demonstrated that booster doses of COVID-19 vaccines, whether heterologous or homologous, are effective in affording seroprotection in patients who were non-responders to the primary series.
Around the world, it has been demonstrated that the vaccine-induced immune response wanes over time, leading to experts to advocate the necessity of a booster dose [38,39]. Hadjadj et al. [27] found that in patients in the cohort that did not receive a booster dose, Alpha and Delta neutralising activity fell by 3.5- and 5-fold, respectively, though anti-spike IgG levels were maintained. While booster doses have, as of current evidence and to the best of our knowledge, not been associated with significant adverse events such as disease flares and mortality, healthcare professionals and policymakers should remain watchful of developing evidence.

4.2. Factors Predicting Non-Response after a Booster Dose

It has been established that anti-CD20 therapies significantly impair seroconversion rate and depress antibody levels even in those who do seroconvert. Our subgroup analysis of patients on anti-CD20 therapy versus those without concurred with this with a significant test for subgroup differences (p-value < 0.0001). Jyssum et al. [24] further determined that patients with a longer duration from last rituximab infusion had better immune responses to vaccines, with a median of 267 days (IQR: 222–324) from last infusion in responders compared to 107 days (IQR: 80–152) in non-responders. This suggests that timing of vaccine doses further from last rituximab infusion to allow time for immune reconstitution may be promising. While withholding immunosuppressive therapy peri-vaccination or timing of vaccinations a set time from last immunosuppressive therapy has been suggested, the evidence for this is not definitive [40,41,42].
Studies of one or two doses of mRNA vaccines demonstrated varying immune response in patients on ocrelizumab [43,44,45] and depressed response in those on belimumab [46]. However, amongst patients studied in this review, rituximab was the main anti-CD20 therapy used and thus we are unable to conclude if other anti-CD20 therapies, such as ocrelizumab, or BLyS-specific inhibitors, such as belimumab, exhibit a similar impaired response. Other than rituximab treatment, Schell et al. [23] determined that anti-TNF therapy may be associated with poorer response.
Immune cell counts, including B-cell, CD4, and CD8 T-cell counts, have been postulated to correlate with immunocompromised patients’ ability to mount a response. Sidler et al. [26] elucidated that patients with higher CD19 counts at baseline may correlated to improved seroconversion, though statistical significance may be limited by a small sample size. Jyssum et al. [24] also found CD19 counts to correlate significantly with response to the second dose.
Patients mounting no response or an undetectable response to the primary vaccine series may be less likely to seroconvert, even if given a booster dose. Connolly et al. [34] found that 80% of the IMID patients who exhibited no detectable response after completion of the primary series seroconverted after the booster. While a majority still seroconverted, this is in contrast to IMID patients with a low-positive response after the primary series, 100% of whom seroconverted.
Another point of optimizing seroconversion rates potentially lies in the choice of COVID-19 vaccine administered as a booster. Schell et al. [23] found that antibody levels were significantly higher in those who received three Moderna doses (Median: 94 [IQR 38–170]) compared to those who received three Pfizer doses (Median: 62 [IQR 31–96]), p-value = 0.047. The idea of heterologous COVID-19 vaccines has been explored in immunocompetent people [47,48,49] as well as other immunocompromised patients such as solid organ transplant recipients [50], but we were unable to elucidate definite evidence of its efficacy in IMID patients.

4.3. Limitations of Review

Firstly, most studies included were observational studies which may not control adequately for factors such as age, disease type, and type of COVID-19 vaccine. To address this, we undertook subgroup analysis according to these factors identified, which suggests there may be significant effect moderation due to vaccine and disease type but not age. IMID patients included in this meta-analysis also were on various immunosuppressive treatments, contributing to heterogeneity in the overall analysis. To address this, we performed subgroup analysis by anti-CD20-containing and non-anti-CD20 regimens, which resulted in little remaining heterogeneity.
Secondly, there is a paucity of published evidence which limited the analysis. Future studies which report data of patients stratified by other treatment factors, such as steroid dose, would allow us to elicit factors predicting poor response to COVID-19 vaccines. Researchers may also seek to further assess the efficacy of heterologous, especially non-mRNA vaccines, as a booster dose, as most patients included in this meta-analysis received the mRNA vaccines BNT162b2 and mRNA-1273.

5. Conclusions

COVID-19 vaccination is one of the foremost preventive strategies against symptomatic and severe infection with COVID-19 in patients receiving immunosuppressive therapy. While non-response to vaccination poses a public health challenge, strategies to mitigate this, such as booster vaccination in non-responders, have been explored. Our systematic review and meta-analysis has shown that booster doses have the propensity to elicit seroconversion in 47% of IMID patients who were non-responders to the primary series of COVID-19 vaccination and with strengthened neutralizing responses to COVID-19 and its emergent variants of significance, including Delta and Omicron. Furthermore, it has not been associated with an increased frequency or severity of adverse events compared to the primary COVID-19 vaccine series.

Supplementary Materials

The following supporting information can be downloaded at: https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/vaccines10050668/s1, Table S1: Search strategy; Table S2: Comparison of characteristics of studies included in meta-analysis; Table S3: Quality assessment of included cohort studies using the Joanna Brigg’s Institute Critical Appraisal tool; Table S4: Quality assessment of included case series using the Joanna Brigg’s Institute Critical Appraisal tool; Table S5: Quality assessment of included randomised-controlled trials using the Joanna Brigg’s Institute Critical Appraisal tool; Figure S1: Trim-and-fill funnel plot with imputation of potentially missing studies; Figure S2: Linear regression test of funnel plot asymmetry; Figure S3: Leave-one-out analysis; Figure S4: Rate of seroconversion after administration of a booster dose in non-responders to a primary series of COVID-19 vaccination using the fixed effects model; Figure S5: Rate of seroconversion after administration of a booster dose in non-responders to a primary series of COVID-19 vaccination using the random effects model with Hartung-Knapp adjustment; Figure S6: Identification and exclusion of outliers.

Author Contributions

Conceptualization, A.R.Y.B.L.; methodology, A.R.Y.B.L. and S.H.T.; software, A.R.Y.B.L.; validation, A.R.Y.B.L. and S.H.T.; formal analysis, A.R.Y.B.L.; investigation, A.R.Y.B.L., S.Y.W. and S.H.T.; data curation, A.R.Y.B.L., S.Y.W. and S.H.T.; writing—original draft preparation, A.R.Y.B.L.; writing—review and editing, A.R.Y.B.L. and S.H.T.; visualization, A.R.Y.B.L.; supervision, S.H.T.; project administration, A.R.Y.B.L.; funding acquisition, S.H.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hyrich, K.L.; Machado, P.M. Rheumatic disease and COVID-19: Epidemiology and outcomes. Nat. Rev. Rheumatol. 2021, 17, 71–72. [Google Scholar] [CrossRef]
  2. Marques, C.D.L.; Kakehasi, A.M.; Pinheiro, M.M.; Mota, L.M.H.; Albuquerque, C.P.; Silva, C.R.; Santos, G.P.J.; Reis-Neto, E.T.; Matos, P.; Devide, G.; et al. High levels of immunosuppression are related to unfavourable outcomes in hospitalised patients with rheumatic diseases and COVID-19: First results of ReumaCoV Brasil registry. RMD Open 2021, 7, e001461. [Google Scholar] [CrossRef] [PubMed]
  3. Furer, V.; Rondaan, C.; Heijstek, M.W.; Agmon-Levin, N.; van Assen, S.; Bijl, M.; Breedveld, F.C.; D’Amelio, R.; Dougados, M.; Kapetanovic, M.C.; et al. 2019 update of EULAR recommendations for vaccination in adult patients with autoimmune inflammatory rheumatic diseases. Ann. Rheum. Dis. 2020, 79, 39–52. [Google Scholar] [CrossRef]
  4. Van Aalst, M.; Langedijk, A.C.; Spijker, R.; de Bree, G.J.; Grobusch, M.P.; Goorhuis, A. The effect of immunosuppressive agents on immunogenicity of pneumococcal vaccination: A systematic review and meta-analysis. Vaccine 2018, 36, 5832–5845. [Google Scholar] [CrossRef] [PubMed]
  5. Firinu, D.; Perra, A.; Campagna, M.; Littera, R.; Fenu, G.; Meloni, F.; Cipri, S.; Sedda, F.; Conti, M.; Miglianti, M.; et al. Evaluation of antibody response to BNT162b2 mRNA COVID-19 vaccine in patients affected by immune-mediated inflammatory diseases up to 5 months after vaccination. Clin. Exp. Med. 2021, 1–9. [Google Scholar] [CrossRef] [PubMed]
  6. Li, P.; Zheng, Y.; Chen, X. Drugs for Autoimmune Inflammatory Diseases: From Small Molecule Compounds to Anti-TNF Biologics. Front. Pharmacol. 2017, 8, 460. [Google Scholar] [CrossRef]
  7. Sepriano, A.; Kerschbaumer, A.; Smolen, J.S.; van der Heijde, D.; Dougados, M.; van Vollenhoven, R.; McInnes, I.B.; Bijlsma, J.W.; Burmester, G.R.; Maarten de Wit, M.; et al. Safety of synthetic and biological DMARDs: A systematic literature review informing the 2019 update of the EULAR recommendations for the management of rheumatoid arthritis. Ann. Rheum. Dis. 2020, 79, 760–770. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Eisenberg, R.A.; Jawad, A.F.; Boyer, J.; Maurer, K.; McDonald, K.; Prak, E.T. Rituximab-treated patients have a poor response to influenza vaccination. J. Clin. Immunol. 2013, 33, 388–396. [Google Scholar] [CrossRef] [Green Version]
  9. Vijenthira, A.; Gong, I.; Betschel, S.D.; Cheung, M.; Hicks, L.K. Vaccine response following anti-CD20 therapy: A systematic review and meta-analysis of 905 patients. Blood Adv. 2021, 5, 2624–2643. [Google Scholar] [CrossRef] [PubMed]
  10. Kelly, H.; Sokola, B.; Abboud, H. Safety and efficacy of COVID-19 vaccines in multiple sclerosis patients. J. Neuroimmunol. 2021, 356, 577599. [Google Scholar] [CrossRef] [PubMed]
  11. Nagel, J.; Saxne, T.; Geborek, P.; Bengtsson, A.A.; Jacobsen, S.; Svaerke Joergensen, C. Treatment with belimumab in systemic lupus erythematosus does not impair antibody response to 13-valent pneumococcal conjugate vaccine. Lupus 2017, 26, 1072–1081. [Google Scholar] [CrossRef] [PubMed]
  12. Friedman, M.A.; Curtis, J.R.; Winthrop, K.L. Impact of disease-modifying antirheumatic drugs on vaccine immunogenicity in patients with inflammatory rheumatic and musculoskeletal diseases. Ann. Rheum. Dis. 2021, 80, 1255–1265. [Google Scholar] [CrossRef] [PubMed]
  13. Barbhaiya, M.; Levine, J.M.; Bykerk, V.P.; Jannat-Khah, D.; Mandl, L.A. Systemic rheumatic disease flares after SARS-CoV-2 vaccination among rheumatology outpatients in New York City. Ann. Rheum. Dis. 2021, 80, 1352–1354. [Google Scholar] [CrossRef] [PubMed]
  14. Lee, A.R.Y.B.; Wong, S.Y.; Chai, L.Y.A.; Lee, S.C.; Lee, M.X.; Muthiah, M.D.; Tay, S.H.; Teo, C.B.; Tan, B.K.J.; Chan, Y.H.; et al. Efficacy of covid-19 vaccines in immunocompromised people: Systematic review and meta-analysis. BMJ 2022, 376, e068632. [Google Scholar] [CrossRef]
  15. Lee, A.R.Y.B.; Wong, S.Y.; Chai, L.Y.A.; Lee, S.C.; Lee, M.; Muthiah, M.D.; Tay, S.H.; Teo, C.B.; Tan, B.K.J.; Chan, Y.H.; et al. Efficacy of COVID-19 vaccines in immunocompromised patients: A systematic review and meta-analysis. medRxiv 2021. [Google Scholar] [CrossRef]
  16. American College of Rheumatology. COVID-19 Vaccine Clinical Guidance Summary for Patients with Rheumatic and Musculoskeletal Diseases. Rheumatology.org. 2022. Available online: https://www.rheumatology.org/Portals/0/Files/COVID-19-Vaccine-Clinical-Guidance-Rheumatic-Diseases-Summary.pdf (accessed on 27 January 2022).
  17. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
  18. Kuek, A.; Hazleman, B.L.; Ostör, A.J. Immune-mediated inflammatory diseases (IMIDs) and biologic therapy: A medical revolution. Postgrad. Med. J. 2007, 83, 251–260. [Google Scholar] [CrossRef] [Green Version]
  19. Munn, Z.; Moola, S.; Riitano, D.; Lisy, K. The development of a critical appraisal tool for use in systematic reviews addressing questions of prevalence. Int. J. Health Policy Manag. 2014, 3, 123–128. [Google Scholar] [CrossRef] [Green Version]
  20. Munn, Z.; Barker, T.H.; Moola, S.; Tufanaru, C.; Stern, C.; McArthur, A. Methodological quality of case series studies: An introduction to the JBI critical appraisal tool. JBI Evid. Synth. 2020, 18, 2127–2133. [Google Scholar] [CrossRef]
  21. Simon, D.; Tascilar, K.; Fagni, F.; Schmidt, K.; Krönke, G.; Kleyer, A.; Ramming, A.; Schoenau, V.; Bohr, D.; Knitza, J.; et al. Efficacy and safety of SARS-CoV-2 revaccination in non-responders with immune-mediated inflammatory disease. Ann. Rheum. Dis. 2021. [Google Scholar] [CrossRef]
  22. Schmiedeberg, K.; Vuilleumier, N.; Pagano, S.; Albrich, W.C.; Ludewig, B.; Kempis, J.V. Efficacy and tolerability of a third dose of an mRNA anti-SARS-CoV-2 vaccine in patients with rheumatoid arthritis with absent or minimal serological response to two previous doses. Lancet Rheumatol. 2022, 4, e11–e13. [Google Scholar] [CrossRef]
  23. Schell, T.L.; Knutson, K.L.; Saha, S.; Wald, A.; Phan, H.S.; Almasry, M.; Chun, K.; Grimes, I.; Lutz, M.; Hayney, M.S.; et al. Humoral Immunogenicity of Three COVID-19 mRNA Vaccine Doses in Patients with Inflammatory Bowel Disease. medRxiv 2021. [Google Scholar] [CrossRef]
  24. Jyssum, I.; Kared, H.; Tran, T.T.; Tveter, A.T.; Provan, S.A.; Sexton, J.; Jørgensen, K.K.; Jahnsen, J.; Kro, G.B.; Warren, D.J.; et al. Humoral and cellular immune responses to two and three doses of SARS-CoV-2 vaccines in rituximab-treated patients with rheumatoid arthritis: A prospective, cohort study. Lancet Rheumatol. 2021, 4, e177–e187. [Google Scholar] [CrossRef]
  25. Speer, C.; Töllner, M.; Benning, L.; Klein, K.; Bartenschlager, M.; Nusshag, C.; Kälble, F.; Reichel, P.; Schnitzler, P.; Zeier, M.; et al. Third COVID-19 vaccine dose with BNT162b2 in patients with ANCA-associated vasculitis. Ann. Rheum. Dis. 2022, 81, 593–595. [Google Scholar] [CrossRef] [PubMed]
  26. Sidler, D.; Born, A.; Schietzel, S.; Horn, M.P.; Aeberli, D.; Amsler, J.; Möller, B.; Njue, L.M.; Medri, C.; Angelillo-Scherrer, A.; et al. Longitudinal analysis of antibody trajectories and humoral responses to a third dose of mRNA vaccines against SARS-CoV-2 in patients with a history of anti-CD20 therapy (RituxiVac 2.0). medRxiv 2021. [Google Scholar] [CrossRef]
  27. Hadjadj, J.; Planas, D.; Ouedrani, A.; Buffier, S.; Delage, L.; Nguyen, Y.; Bruel, T.; Stolzenberg, M.; Staropoli, I.; Ermak, N.; et al. Immunogenicity of BNT162b2 vaccine against the Alpha and Delta variants in immunocompromised patients with systemic inflammatory diseases. Ann. Rheum. Dis. 2022; online ahead of print. [Google Scholar]
  28. Yang, L.M.; Costales, C.; Ramanathan, M.; Bulterys, P.L.; Murugesan, K.; Schroers-Martin, J.; Alizadeh, A.A.; Boyd, S.D.; Brown, J.M.; Nadeau, K.C.; et al. Cell-mediated and humoral immune response to SARS-CoV-2 vaccination and booster dose in immunosuppressed patients. medRxiv 2022. [Google Scholar] [CrossRef]
  29. Bonelli, M.; Mrak, D.; Tobudic, S.; Sieghart, D.; Koblischke, M.; Mandl, P.; Kornek, B.; Simader, E.; Radner, H.; Perkmann, T.; et al. Additional heterologous versus homologous booster vaccination in immunosuppressed patients without SARS-CoV-2 antibody seroconversion after primary mRNA vaccination: A randomised controlled trial. Ann. Rheum. Dis. 2022, 81, 687–694. [Google Scholar] [CrossRef]
  30. Achtnichts, L.; Jakopp, B.; Oberle, M.; Nedeltchev, K.; Fux, C.A.; Sellner, J. Humoral Immune Response after the Third SARS-CoV-2 mRNA Vaccination in CD20 Depleted People with Multiple Sclerosis. Vaccines 2021, 9, 1470. [Google Scholar] [CrossRef]
  31. Madelon, N.; Heikkilä, N.; Sabater Royo, I.; Fontannaz, P.; Breville, G.; Lauper, K.; Goldstein, R.; Grifoni, A.; Sette, A.; Siegrist, C.; et al. Omicron-Specific Cytotoxic T-Cell Responses After a Third Dose of mRNA COVID-19 Vaccine Among Patients with Multiple Sclerosis Treated with Ocrelizumab. JAMA Neurol. 2022, 79, 399–404. [Google Scholar] [CrossRef]
  32. Dreyer-Alster, S.; Menascu, S.; Mandel, M.; Shirbint, E.; Magalashvili, D.; Dolev, M.; Flechter, S.; Givon, U.; Guber, D.; Stern, Y.; et al. COVID-19 vaccination in patients with multiple sclerosis: Safety and humoral efficacy of the third booster dose. J. Neurol. Sci. 2022, 434, 120155. [Google Scholar] [CrossRef]
  33. Mallory, R.; Formica, N.; Pfeiffer, S.; Wilkinson, B.; Marcheschi, A.; Albert, G.; McFall, H.; Robinson, M.; Plested, J.S.; Zhu, M.; et al. Immunogenicity and Safety Following a Homologous Booster Dose of a SARS-CoV-2 recombinant spike protein vaccine (NVX-CoV2373): A Phase 2 Randomized Placebo-Controlled Trial. medRxiv 2021. [Google Scholar] [CrossRef]
  34. Connolly, C.M.; Teles, M.; Frey, S.; Boyarsky, B.J.; Alejo, J.L.; Werbel, W.A.; Albayda, J.; Christopher-Stine, L.; Garonzik-Wang, J.; Segev, D.L.; et al. Booster-dose SARS-CoV-2 vaccination in patients with autoimmune disease: A case series. Ann. Rheum. Dis. 2022, 81, 291–293. [Google Scholar] [CrossRef] [PubMed]
  35. Assawasaksakul, T.; Sathitratanacheewin, S.; Vichaiwattana, P.; Wanlapakorn, N.; Poovorawan, Y.; Kittanamongkolchai, W. Immunogenicity, safety and reactogenicity of a heterogeneous booster following the CoronaVac inactivated SARS-CoV-2 vaccine in patients with SLE: A case series. RMD Open 2021, 7, e002019. [Google Scholar] [CrossRef] [PubMed]
  36. Felten, R.; Gallais, F.; Schleiss, C.; Chatelus, E.; Javier, R.-M.; Pijnenburg, L.; Sordet, C.; Sibilia, J.; Arnaud, L.; Fafi-Kremer, S.; et al. Cellular and humoral immunity after the third dose of SARS-CoV-2 vaccine in patients treated with rituximab. Lancet Rheumatol. 2022, 4, e13–e16. [Google Scholar] [CrossRef]
  37. Kant, S.; Azar, A.; Geetha, D. Antibody response to COVID-19 booster vaccine in rituximab-treated patients with anti-neutrophil cytoplasmic antibody-associated vasculitis. Kidney Int. 2021. [Google Scholar] [CrossRef] [PubMed]
  38. Achiron, A.; Mandel, M.; Dreyer-Alster, S.; Harari, G.; Gurevich, M. Humoral SARS-COV-2 IgG decay within 6 months in COVID-19 healthy vaccinees: The need for a booster vaccine dose? Eur. J. Intern. Med. 2021, 94, 105–107. [Google Scholar] [CrossRef] [PubMed]
  39. Geisen, U.M.; Sümbül, M.; Tran, F.; Berner, D.K.; Reid, H.M.; Vullriede, L.; Ciripoi, M.; Longardt, A.C.; Hoff, P.; Morrison, P.J.; et al. Humoral protection to SARS-CoV2 declines faster in patients on TNF alpha blocking therapies. RMD Open 2021, 7, e002008. [Google Scholar] [CrossRef]
  40. Arnold, J.; Winthrop, K.; Emery, P. COVID-19 vaccination and antirheumatic therapy. Rheumatology 2021, 60, 3496–3502. [Google Scholar] [CrossRef]
  41. Magliulo, D.; Wade, S.D.; Kyttaris, V.C. Immunogenicity of SARS-CoV-2 vaccination in rituximab-treated patients: Effect of timing and immunologic parameters. Clin. Immunol. 2022, 234, 108897. [Google Scholar] [CrossRef]
  42. Elkayam, O.; Bashkin, A.; Mandelboim, M.; Litinsky, I.; Comaheshter, D.; Levartovsky, D.; Mendelson, E.; Wigler, I.; Caspi, D.; Paran, D. The effect of infliximab and timing of vaccination on the humoral response to influenza vaccination in patients with rheumatoid arthritis and ankylosing spondylitis. Semin. Arthritis Rheum. 2010, 39, 442–447. [Google Scholar] [CrossRef]
  43. Brill, L.; Rechtman, A.; Zveik, O.; Haham, N.; Oiknine-Djian, E.; Wolf, D.G.; Levin, N.; Raposo, C.; Vaknin-Dembinsky, A. Humoral and T-Cell Response to SARS-CoV-2 Vaccination in Patients with Multiple Sclerosis Treated with Ocrelizumab. JAMA Neurol. 2021, 78, 1510–1514. [Google Scholar] [CrossRef] [PubMed]
  44. Madelon, N.; Lauper, K.; Breville, G.; Sabater Royo, I.; Goldstein, R.; Andrey, D.O.; Grifoni, A.; Sette, A.; Kaiser, L.; Siegrist, C.; et al. Robust T cell responses in anti-CD20 treated patients following COVID-19 vaccination: A prospective cohort study. Clin. Infect. Dis. 2021. [Google Scholar] [CrossRef] [PubMed]
  45. Guerrieri, S.; Lazzarin, S.; Zanetta, C.; Nozzolillo, A.; Filippi, M.; Moiola, L. Serological response to SARS-CoV-2 vaccination in multiple sclerosis patients treated with fingolimod or ocrelizumab: An initial real-life experience. J. Neurol. 2022, 269, 39–43. [Google Scholar]
  46. Sieiro Santos, C.; Antolin, S.C.; Moriano Morales, C.M.; Herrero, J.G.; Alvarez, E.D.; Ortega, F.R.; de Morales, J.G.R. Immune responses to mRNA vaccines against SARS-CoV-2 in patients with immune-mediated inflammatory rheumatic diseases. RMD Open 2022, 8, e001898. [Google Scholar] [CrossRef]
  47. Munro, A.P.S.; Janani, L.; Cornelius, V.; Aley, P.K.; Babbage, G.; Baxter, D.; Bula, M.; Cathie, K.; Chatterjee, K.; Dodd, K.; et al. Safety and immunogenicity of seven COVID-19 vaccines as a third dose (booster) following two doses of ChAdOx1 nCov-19 or BNT162b2 in the UK (COV-BOOST): A blinded, multicentre, randomised, controlled, phase 2 trial. Lancet 2021, 398, 2258–2276. [Google Scholar] [CrossRef]
  48. Atmar, R.L.; Lyke, K.E.; Deming, M.E.; Jackson, L.A.; Branche, A.R.; Sahly, H.M.E.; Rostad, C.A.; Martin, J.M.; Johnston, C.; Rupp, R.E.; et al. Heterologous SARS-CoV-2 Booster Vaccinations-Preliminary Report. medRxiv 2021. [Google Scholar] [CrossRef]
  49. Zuo, F.; Abolhassani, H.; Du, L.; Piralla, A.; Bertoglio, F.; de Campos-Mata, L.; Wan, H.; Schubert, M.; Wang, Y.; Sun, R.; et al. Heterologous immunization with inactivated vaccine followed by mRNA booster elicits strong humoral and cellular immune responses against the SARS-CoV-2 Omicron variant. medRxiv 2022. [Google Scholar] [CrossRef]
  50. Reindl-Schwaighofer, R.; Heinzel, A.; Mayrdorfer, M.; Jabbour, R.; Hofbauer, T.M.; Merrelaar, A.; Eder, M.; Regele, F.; Doberer, K.; Specht, P.; et al. Comparison of SARS-CoV-2 Antibody Response 4 Weeks After Homologous vs. Heterologous Third Vaccine Dose in Kidney Transplant Recipients: A Randomized Clinical Trial. JAMA Intern. Med. 2022, 182, 165–171. [Google Scholar] [CrossRef]
Figure 1. PRISMA flowchart.
Figure 1. PRISMA flowchart.
Vaccines 10 00668 g001
Figure 2. Rate of seroconversion after administration of a booster dose in non-responders to a primary series of COVID-19 vaccination.
Figure 2. Rate of seroconversion after administration of a booster dose in non-responders to a primary series of COVID-19 vaccination.
Vaccines 10 00668 g002
Table 1. Characteristics of included studies.
Table 1. Characteristics of included studies.
StudyStudy DesignPrimary Series ReceivedBooster VaccineIMIDsTreatment ReceivedSeroconversion ThresholdAge *, YearsDays * between Booster Dose and Primary Series
Simon et al. [21]ObservationalBNT162b2 or AZD1222BNT162b2 or AZD122266 total:5 TNFSARS-CoV-2 spike protein IgG OD450nm > 1.1Mean (SD): 63.3 (14)RTX: 93
Non-RTX: 69
2 IL-17
1 IL-6
1 IL-1
33 RTX
30 RA5 CD80/86
4 SA22 csDMARD
13 CTD30 steroids
14 vasculitis7 JAKi
5 others1 Integrin α4β7
Schmiedeberg et al. [22]ObservationalBNT162b2BNT162b217 RA5 combined csDMARD and biologicsSARS-CoV-2 S1 IgG > 133U/mLNot reportedNot reported
1 csDMARD monotherapy
3 biologic monotherapy
3 JAKi monotherapy
Schell et al. [23]ObservationalBNT162b2 or mRNA-1273BNT62b2 or mRNA-127385 total3 ASAAnti-spike IgG, cutoff not reported48 (38–60)149 (132–167)
55 CD21 vedolizumab monotherapy
6 thiopurine
31 anti-TNF mono
12 anti-TNF combination
30 UC9 ustekinumab monotherapy or combination
2 tofacitinib monotherapy
1 steroids
Jyssum et al. [24]ObservationalBNT162b2 or mRNA-1273BNT162b2 or mRNA-127349 RA16 RTX monotherapyanti-RBD > 70 AU/mL62 (56–67)Not reported
5 steroids
22 MTX
Speer et al. [25]ObservationalBNT162b2BNT162b221 ANCA vasculitis4 only steroidsViral neutralisation > 30%71 (59–74)103
9 Azathioprine or MMF
8 RTX ± azathioprine or MMF ± steroids
Sidler et al. [26]ObservationalBNT162b2BNT162b2 or mRNA-1273Not reportedAnti-CD20 therapies (RTX or ocrelizumab)Anti-SARS-CoV-2 IgG s/c ratio > 1.166 (50–72) (Anti-S1 negative patients)
58 (43–71) (Anti-S1 positive patients)
5 months
Hadjadj et al. [27]ObservationalBNT162b2BNT162b256 total:19 MTXanti-SARS-CoV-2 IgG > 1.1 BAU/mL, IgA > 0.2 BAU/mL52 (37.8–66.3)102
5 azathioprine
18 vasculitis12 MMF
15 SLE3 CYC
7 SS6 anti-TNF
2 Sjogren’s22 RTX
5 myositis3 tocilizumab
3 arthritis1 belimumab
6 others15 HCQ
Yang et al. [28]ObservationalBNT162b2, mRNA-1273 or Ad26.COV2.SBNT162b2, mRNA-1273 or Ad26.COV2.S35 with various IMIDs8 anti-CD20 antibodiesAnti-S1 IgG OD ratio > 1.155 (38–63)Not reported
2 S1P modulators
9 MMF
10 steroids
1 untreated
Bonelli et al. [29]ObservationalBNT162b2 or mRNA-1273BNT162b2, mRNA-1273 or AZD122255 total:10 MTXAnti-RBD IgG > 0.8 BAU/mLPatients receiving viral vector vaccines: 60.9
Patients receiving mRNA vaccines: 58.9
Not reported
6 MMF
21 arthritis5 azathioprine
16 CTD4 leflunamide
8 vasculitis4 HCQ
6 MS2 Ig therapy
4 IgG415 steroids
Achtnichts et al. [30]ObservationalBNT162b2 or mRNA-1273BNT162b2 or mRNA-127316 MS16 RTX or ocrelizumabAnti-RBD > 100 AU/mLMean (SD): 51 (12.3)104.3 (Range: 46–211)
Madelon et al. [31]ObservationalBNT162b2 or mRNA-1273BNT162b2 or mRNA-127320 MS20 ocrelizumabNot reported45.8 (37.8–53.3)187 (156–203)
Dreyer-Alster et al. [32]ObservationalBNT162b2BNT162b2211 MS in total53 untreatedAnti-S1 >35.2 BAU/ml18–55 years: 121
> 55 years: 90
66 (54–84)
6 beta-interferons
2 glatiramer acetate
19 teriflunomide
35 MS with serology data available9 dimethyl fumarate
17 natalizumab
25 fingolimod
65 ocrelizumab
211 MS with safety data available4 alemtuzumab
7 cladribine
1 RTX
3 intravenous immunoglobulins
Mallory et al. [33]Randomised trialNVX-CoV2373NVX-CoV2373VariousVariousInhibition concentration > 50%57189
Connolly et al. [34]Case seriesBNT162b2, mRNA-1273 or Ad26.COV2.SBNT162b2, mRNA-1273 or Ad26.COV2.S18 total:VariousAnti-RBD > 500 U/mL55 (44–65)77
1 MS
2 IBD
6 myositis
1 SLE
2 autoimmune hepatitis
3 arthritis
1 sarcoid
2 others
Assawasaksakul et al. [35]Case seriesCoronaVacBNT162b2 or AZD12228 SLEAzathioprine, cyclosporin, MMF, steroids, tacrolimusInhibition > 35%28 (22–45.5)92
Felten et al. [36]Case seriesBNT162b2, mRNA-1273 or AZD1222BNT162b2 or mRNA-127310 total:RTX-containing regimensAnti-RBD IgG > 7.1 AU/mL72 (67–79.5)65
9 RA
1 Stiff-person syndrome
Kant et al. [37]Case seriesBNT162b2, mRNA-1273 or Ad26.COV2.SBNT162b2, mRNA-1273 or Ad26.COV2.S15 ANCA vasculitisRTX-containing regimensAnti-spike S1 IgG, cutoff not reported69 (63.5–73)Not reported
* Median (IQR) reported if available. Abbreviations: NR, non-responders after primary series; CTD, connective tissue disease; MS, multiple sclerosis; RA, rheumatoid arthritis; SA, spondyloarthritis; CD, Crohn’s disease; UC, ulcerative colitis; SLE, systemic lupus erythematosus; ANCA vasculitis, antineutrophil cytoplasmic antibody vasculitis; RTX, rituximab; MTX, methotrexate; JAKi, Janus kinase inhibitor; ASA, aminosalicylate.
Table 2. Subgroup analysis according to key categorical variables.
Table 2. Subgroup analysis according to key categorical variables.
VariableCohortsN in SubgroupPooled Risk with Random Effects (95% CI)I2 (%)Test for Subgroup Effect (p-Value)
Treatment
Anti-CD2092260.25 (0.17–0.36)50.7< 0.0001
Non-anti-CD2061140.81 (0.72–0.87)0.0
Disease
Only RA3760.51 (0.12–0.89)90.00.0286
Only SLE180.94 (0.50–1.00)NIL
Only ANCA vasculitis2360.53 (0.37–0.68)0.0
Only MS1160.06 (0.01–0.34)NIL
Age
<50180.94 (0.50–1.00)NIL0.0571
50–6572690.36 (0.20–0.56)86.8
>653460.52 (0.38–0.66)0.0
Vaccine type
Only mRNA61630.34 (0.16–0.58)83.50.0049
Only viral vector1270.22 (0.10–0.41)NIL
Abbreviations: RR, risk ratio; CI, confidence interval.
Table 3. Antibody levels after completion of primary series of COVID-19 vaccination and a booster dose.
Table 3. Antibody levels after completion of primary series of COVID-19 vaccination and a booster dose.
Study *Antibody and Value MeasuredDays Post Primary SeriesPre-Booster Titre (IQR) Days Post BoosterPost-Booster Titre (IQR) Fold Increase
Schmiedeberg et al. [22]Anti-S1 antibody level (U/mL)-19.5 (0.45–48)142500 (798–2500)128.21
Schell et al. [23]Anti-RBD antibody titre32 (29–34)31 (16–61)37 (32–47)68 (32–147)2.19
Jyssum et al. [24]Anti-RBD antibody titre (AU/mL)7–103 (2–18)21Rise: 0.96 (0.05–27.38)-
Speer et al. [25]Anti-S1 IgG index103 (72–126)0.1 (0.1–1.8)215.6 (0.5–150)56
Speer et al. [25]Neutralising surrogate antibodies103 (72–126)9 (0–35)2156 (4–94)6.2
Yang et al. [28]Anti-S1 antibody (OD ratio)141.2 (0.2–5.2)At least 73.3 (1.0–7.9)2.75
Yang et al. [28]ACE2 blocking (%)140.0 (0.0–10.2)At least 79.0 (0.0–42.5)NA
Madelon et al. [31]Anti-RBD antibody titre (U/mL)-GMT: 3.530GMT: 57.916.5
Dreyer-Alster et al. (Cladribine) [32]Anti-S1 antibody titre (BAU/mL)At least 6 monthsGMT: 686.30–3 monthsGMT: 2345.63.42
Dreyer-Alster et al. (Glatiramer acetate) [32]Anti-S1 antibody titre (BAU/mL)At least 6 monthsGMT: 581.90–3 monthsGMT: 2530.14.35
Dreyer-Alster et al. (Diroximelfumarate) [32]Anti-S1 antibody titre (BAU/mL)At least 6 monthsGMT: 335.70–3 monthsGMT: 5830.417.37
Dreyer-Alster et al. (Immunoglobulins) [32]Anti-S1 antibody titre (BAU/mL)At least 6 monthsGMT: 145.80–3 monthsGMT: 5077.434.82
Dreyer-Alster et al. (Natalizumab) [32]Anti-S1 antibody titre (BAU/mL)At least 6 monthsGMT: 286.60–3 monthsGMT: 2161.47.54
Dreyer-Alster et al. (Dimethyl fumarate) [32]Anti-S1 antibody titre (BAU/mL)At least 6 monthsGMT: 181.80–3 monthsGMT: 2255.612.41
Dreyer-Alster et al. (Teriflunomide) [32]Anti-S1 antibody titre (BAU/mL)At least 6 monthsGMT: 373.70–3 monthsGMT: 2331.26.24
Mallory et al. [33]Serum IgG against ancestral SARS-CoV-2 (EU)1443905282043674.65
Connolly et al. [34]Anti-RBD antibody level (U/mL)77<0.4 (<0.4–222)30 (27–36)2500 (885–2500)>6250
Assawasaksakul et al. [35]Anti-RBD antibody level (U/mL)-83.3 (31.6–341.6)1419,986 (15,079–59,735)239.93
* Includes data from all participants irrespective of serological status after primary series. Median and interquartile ranges reported unless otherwise stated. Interquartile range unless otherwise stated. Abbreviations: RBD, receptor-binding domain; GMT, geometric mean titre.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Lee, A.R.Y.B.; Wong, S.Y.; Tay, S.H. Booster COVID-19 Vaccines for Immune-Mediated Inflammatory Disease Patients: A Systematic Review and Meta-Analysis of Efficacy and Safety. Vaccines 2022, 10, 668. https://0-doi-org.brum.beds.ac.uk/10.3390/vaccines10050668

AMA Style

Lee ARYB, Wong SY, Tay SH. Booster COVID-19 Vaccines for Immune-Mediated Inflammatory Disease Patients: A Systematic Review and Meta-Analysis of Efficacy and Safety. Vaccines. 2022; 10(5):668. https://0-doi-org.brum.beds.ac.uk/10.3390/vaccines10050668

Chicago/Turabian Style

Lee, Ainsley Ryan Yan Bin, Shi Yin Wong, and Sen Hee Tay. 2022. "Booster COVID-19 Vaccines for Immune-Mediated Inflammatory Disease Patients: A Systematic Review and Meta-Analysis of Efficacy and Safety" Vaccines 10, no. 5: 668. https://0-doi-org.brum.beds.ac.uk/10.3390/vaccines10050668

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop