Literature DB >> 35640943

Risk of systemic vasculitis following mRNA COVID-19 vaccination: a pharmacovigilance study.

Camille Mettler1,2, Benjamin Terrier2,3, Jean-Marc Treluyer1,3, Laurent Chouchana1.   

Abstract

Entities:  

Keywords:  COVID-19 vaccine; adverse drug reaction; influenza vaccine; systemic vasculitis

Year:  2022        PMID: 35640943      PMCID: PMC9213846          DOI: 10.1093/rheumatology/keac323

Source DB:  PubMed          Journal:  Rheumatology (Oxford)        ISSN: 1462-0324            Impact factor:   7.046


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Compared with influenza vaccines, systemic vasculitis reporting is not increased with mRNA COVID-19 vaccines, except eventually for Behçet’s syndrome. Dear Editor, Sporadic cases of systemic vasculitis following coronavirus disease 2019 (COVID-19) vaccination were anecdotally reported in the literature [1, 2], raising the question of the association between vasculitis onset and vaccination during the COVID-19 pandemic. We recently showed that GCA and PMR may be associated with COVID-19 vaccines, although risk of reporting these entities appears lower than with influenza vaccines [3]. Here we aimed to assess a potential safety signal for the different types of systemic vasculitis following mRNA COVID-19 vaccination. We used VigiBase (https://www.who-umc.org/vigibase/vigibase/), the World Health Organization (WHO) global individual case safety report database that contains spontaneous reports of suspected adverse drug reactions collected by national drug authorities in >130 countries. This large database is powerful for signal detection based on disproportionality analyses [4, 5]. This pharmacovigilance statistical approach is similar to a case–control study nested in a large cohort [4] and estimates whether an adverse event is differentially reported for a specific drug compared with other drugs. The association between an specific adverse event (i.e. a type of vasculitis) and a specific drug (i.e. mRNA COVID-19 vaccines) was expressed using the reporting odds ratio (ROR) and its 95% CI, which corresponds to the exposure odds among reported cases divided by the exposure odds among reported non-cases. To limit indication and reporting bias, comparators were influenza vaccines. A lower boundary 95% CI >1 is deemed significant, as for OR interpretation, and supports a potential safety signal. This study adhered to the Declaration of Helsinki. Of the 2 499 457 spontaneous reports with mRNA COVID-19 vaccines (i.e. elasomeran/mRNA-1273 and tozinameran/BNT162b2) in VigiBase through 31 March 2022, we identified 2125 (8.5/10 000 reports) vasculitis cases; 61% were women, with median age of 58 years [interquartile range (IQR) 38–72]. Overall, mRNA COVID-19 vaccines were associated with increased reporting in Behçet’s syndrome [ROR 1.7 (95% CI 1.4, 2.1)], GCA [ROR 4.5 (95% CI 4.0, 5.0)], microscopic polyangiitis [ROR 2.6 (95% CI 1.8, 3.7)], livedoid vasculopathy [ROR 4.1 (95% CI 2.5, 6.5)] and urticarial vasculitis [ROR 3.0 (95% CI 2.4, 3.7)] (Table 1). None of the other vasculitis types were associated with increased reporting following mRNA COVID-19 vaccines, especially eosinophilic granulomatosis with polyangiitis, Henoch-Schönlein purpura (i.e. IgA vasculitis) or polyarteritis nodosa. When compared with the use of influenza vaccines, we found a disproportionate reporting with mRNA COVID-19 vaccines only for Behçet’s syndrome [ROR 4.2 (95% CI 1.3, 13.2)], in a similar manner between elasomeran and tozinameran [ROR 1.7 (95% CI 1.0, 2.9)]. Among the 93 Behçet’s syndrome cases, 76 (82%) were women, with a median age of 37 years (IQR 30–43). Differences in systemic vasculitis risk may exist between elasomeran and tozinameran but require further study.
Table 1

Systemic vasculitis cases reported in the WHO global safety database with mRNA COVID-19 vaccines and their reporting ORs

Types of vasculitis N observed a
N expected N reaction Disproportionality analysis, ROR (95% CI)
mRNA COVID-19 vaccinesElasomeranTozinameranmRNA COVID-19 vaccines vs any drugsmRNA COVID-19 vaccines vs influenza vaccinesTozinameran vs elasomeran
ANCA-associated vasculitis2294118825530640.9 (0.8, 1.0)0.4 (0.3, 0.4) 1.8 (1.3, 2.5)
ANCA-positive vasculitis681454759050.9 (0.7, 1.1)0.3 (0.2, 0.5)1.5 (0.8, 2.7)
Eosinophilic granulomatosis with polyangiitis54114310612740.5 (0.4, 0.6)0.4 (0.2, 0.7)1.5 (0.8, 2.9)
Granulomatosis with polyangiitis821666647701.3 (1.0, 1.7)0.3 (0.2, 0.4)1.6 (0.9, 2.7)
Microscopic polyangiitis3433115180 2.6 (1.8, 3.7) 0.5 (0.2, 0.9) 4.0 (1.2, 13.0)
Behçet’s syndrome93177657690 1.7 (1.4, 2.1) 4.2 (1.3, 13.2) 1.7 (1.0, 2.9)
Central nervous system vasculitis47641475681.0 (0.7, 1.3)0.6 (0.3, 1.3) 2.6 (1.1, 6.2)
Cryoglobulinaemic vasculitis38137334011.2 (0.8, 1.6)0.6 (0.3, 1.2)c
Cutaneous vasculitisb74013560574289211.0 (0.9, 1.1)0.5 (0.4, 0.5) 1.7 (1.4, 2.1)
Giant cell arteritis501994021441736 4.5 (4.0, 5.0) 0.7 (0.6, 0.9) 1.6 (1.3, 1.9)
Henoch, Schönlein purpura2565120537044470.7 (0.6, 0.8)0.1 (0.1, 0.1) 1.5 (1.1, 2.1)
Kawasaki’s disease4514411814210.4 (0.3, 0.5)0.1 (0.1, 0.1)c
Liveloid vasculopathy24618789 4.1 (2.5, 6.5) c1.2 (0.5, 2.9)
Polyarteritis nodosa24519647740.4 (0.2, 0.5)0.3 (0.1, 0.5)1.5 (0.5, 3.9)
Takayasu’s arteritis909172010.5 (0.3, 1.0)cc
Urticarial vasculitis and hypocomplementemic urticarial vasculitis syndrome93197437439 3.0 (2.4, 3.7) 1.1 (0.6, 2.1)1.5 (0.9, 2.5)

The specific types of vasculitis were identified using the ad hoc preferred terms from the Medical Dictionary for Regulatory Activities (MedDRA; https://www.meddra.org/). ROR (95% CI) were calculated as , where a is the number of cases reported with RNA-based COVID-19 vaccines, b is the number of non-cases (i.e. all other adverse drug reaction reports) reported with RNA-based COVID-19 vaccines, c is the number of cases reported with all other drugs and d is the number of non-cases reported with all other drugs. The threshold for signal detection is defined as an ROR lower boundary 95% CI ≥1 and the number of cases ≥3. Significant associations (adverse event–drug combination) are presented in bold. Nexpected is the expected number of case reports based on the number of case reports for the drug and for the specific reaction, calculated as (Ndrug × Nreaction)/Ntotal, with Ntotal being the total number of reports in the database with any drugs (i.e. 30 031 000 reports) and Ndrug being the number of reports for the drug, regardless the type of reaction (i.e. 2 499 457 reports with elasomeran or tozinameran); Nreaction is the number of reports for the reaction (i.e. cases), regardless of drug.

The sum of Nobserved is greater than the number of cases, as one case may refer to more than one type of vasculitis.

Refers to hypersensitivity vasculitis, palpable purpura, vasculitic rash and vasculitic ulcer.

ROR not provided because insufficient cases were observed with the studied drugs.

Systemic vasculitis cases reported in the WHO global safety database with mRNA COVID-19 vaccines and their reporting ORs The specific types of vasculitis were identified using the ad hoc preferred terms from the Medical Dictionary for Regulatory Activities (MedDRA; https://www.meddra.org/). ROR (95% CI) were calculated as , where a is the number of cases reported with RNA-based COVID-19 vaccines, b is the number of non-cases (i.e. all other adverse drug reaction reports) reported with RNA-based COVID-19 vaccines, c is the number of cases reported with all other drugs and d is the number of non-cases reported with all other drugs. The threshold for signal detection is defined as an ROR lower boundary 95% CI ≥1 and the number of cases ≥3. Significant associations (adverse event–drug combination) are presented in bold. Nexpected is the expected number of case reports based on the number of case reports for the drug and for the specific reaction, calculated as (Ndrug × Nreaction)/Ntotal, with Ntotal being the total number of reports in the database with any drugs (i.e. 30 031 000 reports) and Ndrug being the number of reports for the drug, regardless the type of reaction (i.e. 2 499 457 reports with elasomeran or tozinameran); Nreaction is the number of reports for the reaction (i.e. cases), regardless of drug. The sum of Nobserved is greater than the number of cases, as one case may refer to more than one type of vasculitis. Refers to hypersensitivity vasculitis, palpable purpura, vasculitic rash and vasculitic ulcer. ROR not provided because insufficient cases were observed with the studied drugs. Here we used the WHO global safety database to assess potential safety signals for the different types of systemic vasculitis following the use of mRNA COVID-19 vaccines. We found an increased reporting of Behçet’s syndrome, microscopic polyangiitis, livedoid vasculopathy and urticarial vasculitis and, as previously reported, GCA following mRNA COVID-19 vaccination. These findings suggest a potential safety signal for these entities. It should be noted that we previously showed the relative risk for GCA or PMR reporting was reduced with COVID-19 vaccines when the comparator was influenza vaccines [3]. Here, for all vasculitis types except Behçet’s syndrome, we did not find increased reporting when compared with influenza vaccines. Behçet’s syndrome cases were in the range of the expected epidemiology of this disease. Although significant, these results should be interpreted with caution considering the small number of cases in the comparator group. Environmental factors and infections are likely to play a role in the onset of systemic vasculitis and vaccination could act as an inflammatory trigger, as already suspected in previous studies [6]. Our analysis has limitations such as a underreporting and heterogeneous causality assessment among reports. Also, it highlights the importance of using a relevant comparator for the interpretation of these real-life data. Overall, our study did not suggest a specific vasculitis risk with mRNA COVID-19 vaccines compared with influenza vaccines, except eventually for Behçet’s syndrome. Further analyses are needed to confirm this safety signal and vaccine causality. Nevertheless, mRNA COVID-19 vaccine benefits dramatically outweigh this potential risk, which appears very rare relative to the billions of doses administered so far.
  6 in total

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Authors:  Kenneth J Rothman; Stephan Lanes; Susan T Sacks
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2.  Benefits and strengths of the disproportionality analysis for identification of adverse drug reactions in a pharmacovigilance database.

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3.  Risk of giant cell arteritis and polymyalgia rheumatica following COVID-19 vaccination: a global pharmacovigilance study.

Authors:  Camille Mettler; Annie-Pierre Jonville-Bera; Aurélie Grandvuillemin; Jean-Marc Treluyer; Benjamin Terrier; Laurent Chouchana
Journal:  Rheumatology (Oxford)       Date:  2022-02-02       Impact factor: 7.580

Review 4.  Drug-induced IgA vasculitis in children and adults: Revisiting drug causality using a dual pharmacovigilance-based approach.

Authors:  Camille Rasmussen; Mylène Tisseyre; Julie Garon-Czmil; Marina Atzenhoffer; Loic Guillevin; Joe-Elie Salem; Jean-Marc Treluyer; Benjamin Terrier; Laurent Chouchana
Journal:  Autoimmun Rev       Date:  2020-11-14       Impact factor: 9.754

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