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)
Types of vasculitis	mRNA COVID-19 vaccines	Elasomeran	Tozinameran	N _expected	N _reaction	mRNA COVID-19 vaccines vs any drugs	mRNA COVID-19 vaccines vs influenza vaccines	Tozinameran vs elasomeran
ANCA-associated vasculitis	229	41	188	255	3064	0.9 (0.8, 1.0)	0.4 (0.3, 0.4)	1.8 (1.3, 2.5)
ANCA-positive vasculitis	68	14	54	75	905	0.9 (0.7, 1.1)	0.3 (0.2, 0.5)	1.5 (0.8, 2.7)
Eosinophilic granulomatosis with polyangiitis	54	11	43	106	1274	0.5 (0.4, 0.6)	0.4 (0.2, 0.7)	1.5 (0.8, 2.9)
Granulomatosis with polyangiitis	82	16	66	64	770	1.3 (1.0, 1.7)	0.3 (0.2, 0.4)	1.6 (0.9, 2.7)
Microscopic polyangiitis	34	3	31	15	180	2.6 (1.8, 3.7)	0.5 (0.2, 0.9)	4.0 (1.2, 13.0)
Behçet’s syndrome	93	17	76	57	690	1.7 (1.4, 2.1)	4.2 (1.3, 13.2)	1.7 (1.0, 2.9)
Central nervous system vasculitis	47	6	41	47	568	1.0 (0.7, 1.3)	0.6 (0.3, 1.3)	2.6 (1.1, 6.2)
Cryoglobulinaemic vasculitis	38	1	37	33	401	1.2 (0.8, 1.6)	0.6 (0.3, 1.2)	–^c
Cutaneous vasculitis^b	740	135	605	742	8921	1.0 (0.9, 1.1)	0.5 (0.4, 0.5)	1.7 (1.4, 2.1)
Giant cell arteritis	501	99	402	144	1736	4.5 (4.0, 5.0)	0.7 (0.6, 0.9)	1.6 (1.3, 1.9)
Henoch, Schönlein purpura	256	51	205	370	4447	0.7 (0.6, 0.8)	0.1 (0.1, 0.1)	1.5 (1.1, 2.1)
Kawasaki’s disease	45	1	44	118	1421	0.4 (0.3, 0.5)	0.1 (0.1, 0.1)	–^c
Liveloid vasculopathy	24	6	18	7	89	4.1 (2.5, 6.5)	–^c	1.2 (0.5, 2.9)
Polyarteritis nodosa	24	5	19	64	774	0.4 (0.2, 0.5)	0.3 (0.1, 0.5)	1.5 (0.5, 3.9)
Takayasu’s arteritis	9	0	9	17	201	0.5 (0.3, 1.0)	–^c	–^c
Urticarial vasculitis and hypocomplementemic urticarial vasculitis syndrome	93	19	74	37	439	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 $\frac{a d}{b c} {(\frac{a d}{b c} . e}^{\pm 1.96 \sqrt{(\frac{1}{a} + \frac{1}{b} + \frac{1}{c} + \frac{1}{d})}})$ , 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. N_expected is the expected number of case reports based on the number of case reports for the drug and for the specific reaction, calculated as (N_drug × N_reaction)/N_total, with N_total being the total number of reports in the database with any drugs (i.e. 30 031 000 reports) and N_drug being the number of reports for the drug, regardless the type of reaction (i.e. 2 499 457 reports with elasomeran or tozinameran); N_reaction is the number of reports for the reaction (i.e. cases), regardless of drug.

The sum of N_observed 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.