Interstitial lung disease following COVID-19 vaccination: a disproportionality analysis using the Global Scale Pharmacovigilance Database (VigiBase)

LeeM- T, etal. BMJ Open Respir Res 2023;10:e001992. doi:10.1136/bmjresp-2023-001992

To cite: LeeM- T, LeeJW,

LeeHJ, etal. Interstitial lung

disease following COVID- 19

vaccination: a disproportionality

analysis using the Global Scale

Pharmacovigilance Database

(VigiBase). BMJ Open Respir

Res 2023;10:e001992.

doi:10.1136/

bmjresp-2023-001992

► Additional supplemental

material is published online

only. To view, please visit the

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001992).

Received 31 July 2023

Accepted 14 November 2023

For numbered affiliations see

end of article.

Correspondence to

Dr Sun- Young Jung;

jsyoung@ cau. ac. kr

Interstitial lung disease following

COVID- 19 vaccination: a

disproportionality analysis using the

Global Scale Pharmacovigilance

Database (VigiBase)

Min- Taek Lee,

1,2

Ju Won Lee,

1,2

Hyeon Ji Lee,

1,2

Jong- Min Lee,

1,2

Jae Chol Choi,

3,4

Kang- Mo Gu,

4,5

Sun- Young Jung

Interstitial lung disease

employer(s)) 2023. Re- use

permitted under CC BY- NC. No

commercial re- use. See rights

and permissions. Published by

BMJ.

ABSTRACT

Background and objective Despite several case reports,

population- based studies on interstitial lung disease (ILD)

following COVID- 19 vaccination are lacking. Given the

unprecedented safety issue of COVID- 19 vaccination,

it is important to assess the worldwide patterns of ILD

following COVID- 19 vaccination. This study aimed to

investigate the signals of COVID- 19 vaccine- associated ILD

compared with other vaccinations using disproportionality

analysis.

Methods We analysed the VigiBase database during the

period between 13 December 2020 and 26 January 2023.

We adopted the case/non- case approach to assess the

disproportionality signal of ILD for COVID- 19 vaccines via

1:10 matching by age and sex. We compared COVID- 19

vaccines with all other vaccines as the reference group.

Results Among 1 233 969 vaccine- related reports, 679

were reported for ILD. The majority of ILD cases were

related to tozinameran (376 reports, 55.4%), Vaxzevria

(129 reports, 19.0%) and elasomeran (78 reports, 11.5%).

The reporting OR of ILD following COVID- 19 vaccination

was 0.86 (95% CI 0.64 to 1.15) compared with all other

vaccines.

Conclusion No signicant signal of disproportionate

reporting of ILD was observed for COVID- 19 vaccines

compared with all other vaccines. Moreover, when

compared with the inuenza vaccines that are known

to cause ILD, no signal was observed. This study results

might help decision- making on the subsequent COVID- 19

vaccination strategy of ILD. Further large and prospective

studies are required for more conclusive evidence.

INTRODUCTION

As of September 2023, a total of 13.5 billion

doses of COVID- 19 vaccines have been

administered, which averted millions of death

worldwide.

1 2

The World Health Organization

(WHO) has recently declared the expira-

tion of COVID- 19 public health emergency

and revise the long- term COVID- 19 disease

management strategies.

It is expected that

the COVID- 19 vaccines will be included in

the regular immunisation schedule similar

to other seasonal influenza vaccines.

4 5

ensure a successful vaccination programme,

safety information is important, especially for

concerns that are not fully addressed. WHO

encourages countries to perform research

on vaccines with respect to unknown critical

information.

Since August 2021, cases of interstitial lung

disease (ILD) following COVID- 19 vaccina-

tion have been reported, although the under-

lying aetiology remained poorly understood.

ILD is a heterogeneous group of diseases

characterised by progressive inflammation

and injury to the interstitium and alveoli.

6 7

The incidence of ILD varies according to age,

sex, region and race and the prevalence is

WHAT IS ALREADY KNOWN ON THIS TOPIC

⇒ Since the rst case report of interstitial lung disease

(ILD) following COVID- 19 vaccination was published

on 9 June 2021, several ILD cases have been re-

ported. However, population- based studies on ILD

following COVID- 19 vaccination are lacking.

WHAT THIS STUDY ADDS

⇒ No signicant signal of disproportionate reporting of

ILD was observed for COVID- 19 vaccines compared

with other vaccines (reporting OR 0.86, 95% CI 0.64

to 1.15). These ndings were consistent across sev-

eral analyses conducted after considering potential

biases.

HOW THIS STUDY MIGHT AFFECT RESEARCH,

PRACTICE OR POLICY

⇒ This study may provide information that can be use-

ful for making decisions on subsequence COVID- 19

vaccine strategies. Moreover, further studies using

patient- level information such as disease history

and diagnostic test results are required for more

conclusive evidence.

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approximately 6.3–76.0 cases per 100 000 people.

8 9

The

causes of ILD are not clearly known, but several poten-

tial risk factors have been suggested, including systemic

autoimmune disease and drug exposure.

The incidence

and prevalence of drug- induced ILD are not well known;

however, approximately 2.5%–5.0% of all prevalent ILD

cases are estimated to be drug induced.

10 11

Amiodarone

and methotrexate are known to cause drug- induced ILD,

and the use of these medications has been reported in

over 10% of cases with mortality.

According to previous

reports, vaccination, especially for influenza, is likely to

cause ILD.

12–14

Conversely, there have been some case

reports suggesting an association between COVID- 19

vaccination and the development and progression

of ILD.

15–22

It remains unknown whether COVID- 19

vaccination- associated ILD has distinct characteristics

compared with the disease induced by other vaccines,

such as the influenza vaccine.

Spontaneous reports are a useful source to assess

signals of rare but serious adverse events (AEs), including

COVID- 19 vaccine- induced ILD. Studies suggest a tempo-

rary increase in reporting rate after product approval

and safety alerts due to safety concerns. Therefore, it is

necessary to verify ILD cases as the COVID- 19 vaccination

rate increases. Given that the unprecedented safety issues

of COVID- 19 vaccines have been raised, it is important

to study the identifying characteristics of ILD following

COVID- 19 vaccination and investigate factors affecting

the risk of ILD or reporting rate. Therefore, this study

aimed to assess the disproportionality of reporting of

ILD associated with COVID- 19 vaccines using the case/

non- case approach by analysing the WHO global phar-

macovigilance database.

METHODS

Data source

We used VigiBase, the largest global pharmacovigilance

database with over 30 million reports of suspected AEs

of medicines since 1968.

It was developed and main-

tained by WHO- Uppsala Monitoring Centre (UMC).

The WHO- UMC receives individual case safety reports

(ICSRs) from over 150 countries participating in the

WHO programme for international drug monitoring.

VigiBase is composed of several medical and drug clas-

sification elements, such as the medical dictionary for

regulatory activities (MedDRA) and WHODrug. The AEs

analysed in our study were investigated using MedDRA

version 26.0 (released March 2023) with preferred terms

(PTs) and lowest level terms (LLTs), and drugs were

coded using WHODrug Global B3/C3- format 1 March

2023.

Variables

We extracted the ICSRs with vaccines as suspected drugs

between 13 December 2020 and 26 January 2023.

ILD was defined using MedDRA- standardised MedDRA

queries (SMQ) (SMQ code=20000042) narrow terms

to provide a clear definition and to account for speci-

ficity (cases highly likely to be of interest). There were

79 PTs and 132 LLTs in the ILD defined by MedDRA

SMQ (online supplemental table 1). The COVID- 19

vaccines tozinameran, elasomeran, Vaxzevria, Ad26.

COV2.S, Gam- COVID- Vac, NVX- CoV2373 and GBP510

were included in our study and were defined using drug

record numbers in WHODrug (online supplemental

table 2) and the Anatomical Therapeutic Chemical

(ATC) classification (J07BN). The other vaccines were

classified according to ATC classification (J07; vaccines).

We included physicians, pharmacists and other health

professionals as notifier types, and excluded reports with

missing values, including age and sex. The dates on which

the reports were entered into the VigiBase were arranged

by quarters. The geographical regions were divided

into five groups: Africa, the Americas, South- East Asia,

Europe, Eastern Mediterranean and Western Pacific.

Using ICSRs, we calculated the time- to- onset, which is the

time interval between vaccine administration and initi-

ation of the event. In VigiBase, ICSRs contain multiple

AEs with several different time- to- onset. Therefore, we

selected the vaccine- AE pairs with the most information,

including dechallenge action/outcome and rechallenge

action/outcome as representatives. Moreover, if vaccine–

AE pairs have an equal number of outcome informa-

tion, we chose the ICSR with the shortest time- to- onset.

Furthermore, we regarded time- to- onset as an outlier by

individual pairs (coded as missing values) if it was outside

the study period.

Statistical analysis

We performed a descriptive analysis of ILD cases and

non- cases. Continuous variables, including time- to- onset,

were presented as the mean±SD and were compared using

the Student’s t- test. The categorical variables, including

reported quarter, age groups, sex, type of report, type

of COVID- 19 vaccines, seriousness, region and type of

notifier, were reported as numbers (percentage) and

compared using the χ

test and Fisher’s exact test.

The association between COVID- 19 vaccines and

ILD was evaluated using case/non- case analysis.

The

case/non- case analysis is a disproportionality approach

performed in the pharmacovigilance databases devel-

oped during the early 1980s.

Briefly, it is similar to case–

control analysis but uses non- case instead of control. In

the spontaneous AE report database, the ICSRs indi-

cate reports of exposure to the drug of interest at least

once and any AE experienced any AE at least once.

our study, cases were defined as ICSRs of ILD while the

remaining ICSRs were considered non- cases. The primary

analysis compared the COVID- 19 vaccines with all other

vaccines. We compared ILD cases and non- cases by 1:10

matching according to age and sex as matching variables.

The logistic regression model was used for calculating

reporting ORs (RORs) and 95% CI.

We determined the

detection of a signal according to the three criteria: the

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Open access

ROR is greater than 1, the lower bound 95% CI is greater

than 1 and the number of cases is greater than 3.

We performed subgroup analyses using stratification

by age groups, sex and region. We determined factors

reported in previous case reports that may affect the

occurrence of ILD. Individuals were categorised into

two groups based on (1) age (<65 and ≥ 65 years), (2)

sex (male and female) and (3) region (Western Pacific

region and the other regions).

Moreover, sensitivity analyses were performed to iden-

tify diverse AE definitions and the extent of contribution

of potential biases as follows. First, we designed sensitivity

analysis 1 to define ICSRs with vaccines as suspected,

concomitant and interaction drugs, as opposed to the

primary analysis performed with suspected drugs. Second,

we defined ILD using both MedDRA SMQ narrow and

broad terms (broad search), thereby including all

possible cases. Third, we excluded ICSRs that included

drugs known to cause ILD, such as those used to treat

cancer, rheumatic diseases, infection and cardiac diseases

(online supplemental table 2) as these can influence

the likelihood of detecting a signal between COVID- 19

vaccines (drug competition bias).

Fourth, since events

known as scientific and specific medical concerns about

COVID- 19 vaccines could affect other signal events

(competition bias), we excluded reports containing 14

AEs of special interest of COVID- 19 vaccine, including

myocarditis, pericarditis and thrombosis, as suggested by

Brighton collaboration.

Fifth, ICSRs reported as serious

AEs were restricted in sensitivity analysis 5. The Weber

effect could arise due to the market authorisation of

new COVID- 19 vaccines. Sixth, we included ICSRs with

a reporting date before 9 August 2021, which may have

influenced reporting in sensitivity analysis 6 (notoriety

bias).

Finally, in sensitivity analysis 7, we compared the

COVID- 19 vaccines with the influenza vaccines (ATC:

J07BB, influenza vaccines) as a positive control. This

choice was based on previous reports

12–14

indicating that

influenza vaccines have been known to cause ILD. Addi-

tionally, there is a report suggesting that the mechanism

of ILD following COVID- 19 vaccination may be similar to

the mechanism of ILD following influenza vaccination.

We have organised the overall analysis strategies in online

supplemental table 3.

Patient and public involvement

As this is a secondary database study, the database is

anonymised and served without identifiers of the study

participants. The patients were not involved in the

design, conduct or dissemination of this study.

RESULTS

A total of 1 233 969 reports with AEs following COVID- 19

vaccination were identified from 12 December 2020 to

26 January 2023. After 1:10 matching by age group and

sex, 7469 reports were determined to be ILD cases (679

ICSRs) and non- cases (6790 ICSRs) (figure 1). The

characteristics of ILD cases/non- cases of the primary

analysis, including reported quarter, age groups, sex, type

of report, type of vacines, seriousness, region and time-

to- onset, are shown in table 1. This study analysed six

COVID- 19 vaccines, including tozinameran, elasomeran,

Vaxzevria, Ad26.COV2.S., Gam- COVID- Vac and NVX-

CoV2373. GBP510 was not included in our study. Most

of the reports were received in the third quarter of 2021

(104 ICSRs, 17.1%) with ILD cases following COVID- 19

vaccination being first reported (table 1). A significant

proportion of ILD cases received tozinameran (376

ICSRs, 55.4%) and were Europeans (577 reports, 85.0%).

Serious AEs including death, life- threatening conditions

and hospitalisation/prolonged hospitalisation were

more likely in ILD cases (625 ICSRs, 92.1%) compared

with non- cases (2343 ICSRs, 34.5%). ILD cases had the

highest proportion of reports received by physicians (527

ICSR, 77.6%), followed by other health professionals

(102 ICSRs, 105.8%) and pharmacists (50 ICSRs, 7.4%).

The median time- to- onset was 7 (IQR 1–36) days for ILD

cases and 1 (IQR 0–15) day for non- cases (p=0.0077).

The number of monthly ILD cases following COVID- 19

vaccination is shown in figure 2. Most of the cases of

ILD following COVID- 19 vaccination (40 cases) were

Figure 1 Flow chart of primary analysis. Primary analysis

compared COVID- 19 vaccines with all other vaccines.

ICSR, individual case safety report; ILD, interstitial lung

disease; MedDRA, Medical Dictionary for Regulatory

Activities.

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Open access

Table 1 Characteristics of interstitial lung disease (ILD) and non- ILD cases from VigiBase database: primary analysis

(compared COVID- 19 vaccines with all other vaccines)

ILD cases (N=679) Non- cases (N=6790)

P valueN (%) N (%)

Reported quarter (Q) 0.036

2020.4Q (13 December 2020–31 December 2020) 0 (0.0) 19 (0.3)

2021.1Q (1 January 2021–31 March 2021) 49 (7.2) 703 (10.4)

2021.2Q (1 April 2021–30 June 2021) 104 (15.3) 1193 (17.6)

2021.3Q (1 July 2021–30 September 2021) 116 (17.1) 1066 (15.7)

2021.4Q (1 October 2021–31 December 2021) 104 (15.3) 1002 (14.8)

2022.1Q (1 January 2022–31 March 2022 102 (15.0) 883 (13.0)

2022.2Q (1 April 2022–30 June 2022) 80 (11.8) 820 (12.1)

2022.3Q (1 July 2022–30 September 2022) 44 (6.5) 463 (6.8)

2022.4Q (1 October 2022–31 December 2022) 66 (9.7) 560 (8.3)

2023.1Q (1 January 2023–26 January 2023) 14 (2.1) 81 (1.2)

Age groups 1

0–27 days 2 (0.3) 20 (0.3)

28 days to 23 months 26 (3.8) 260 (3.8)

2–11 years 4 (0.6) 40 (0.6)

12–17 years 4 (0.6) 40 (0.6)

18–44 years 92 (13.6) 920 (13.6)

45–64 years 187 (27.5) 1870 (27.5)

65–74 years 144 (21.2) 1440 (21.2)

≥75 years 220 (32.4) 2200 (32.4)

Sex 1

Male 356 (52.4) 3560 (52.4)

Female 323 (47.6) 3230 (47.6)

Report type <0.0001

Spontaneous 618 (91.0) 6205 (91.4)

Report from study 54 (8.0) 317 (4.7)

Other 7 (1.0) 267 (3.9)

Not available to sender (unknown) 0 (0.0) 1 (0.0)

Vaccines type

COVID- 19 vaccines 626 (92.2) 6331 (93.2) 0.3039

Tozinameran 376 (55.4) 3324 (49.0) 0.0014

Elasomeran 78 (11.5) 642 (9.5) 0.0871

Vaxzevria 129 (19.0) 1492 (22.0) 0.073

Ad26.COV2.S 8 (1.2) 224 (3.3) 0.0024

Gam- COVID- Vac 0 (0.0) 2 (0.0) 0.6547

NVX- CoV2373 0 (0.0) 3 (0.0) 1.000

Inuenza vaccines 34 (5.0) 123 (1.8) <0.0001

Pneumococcal vaccines 11 (1.6) 105 (1.6) 0.8824

Drug known to cause ILD included in the ICSRs*

Cancer therapy 17 (2.5) 10 (0.2) <0.0001

Rheumatology therapy 27 (4.0) 25 (0.4) <0.0001

Anti- infection agent 3 (0.4) 3 (0.0) 0.0121

Cardiology drugs 62 (9.1) 241 (3.6) <0.0001

Continued

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reported in September 2021, while the first report was

from January 2021. The number of reports decreased

steadily until the end of the study. Serious AE reports

accounted for 84.4% to 100% of all ILD cases following

COVID- 19 vaccination (figure 2).

We identified characteristics of ILD cases by COVID- 19

vaccines, influenza vaccines and other vaccines. The

COVID- 19 vaccines contained reports from European

and had the longest median time- to- onset (1 (IQR 1–36)

day) than the influenza vaccine (5 (IQR 2–23)) and others

(6 (IQR 1–21)) (online supplemental table 4). The most

frequently reported AEs with regard to PT or LLT were

pneumonitis (134 ICSRs, 19.7%), ILD (70 ICSRs, 10.3%)

and interstitial pneumonia (46 ICSRs, 6.8%) in ILD cases

(online supplemental table 5). AEs that included both

narrow and broad terms were aligned with the AEs from

narrow terms. Details of ILD cases are provided in online

supplemental tables 4 and 5.

Case/non-case analysis

The results of ILD cases/non- cases, including those of

primary, secondary and subgroup analyses, are shown in

table 2. The ROR of ILD following COVID- 19 vaccina-

tion was 0.86 (95% CI 0.64 to 1.15) compared with other

vaccines. The ROR of mRNA vaccines was 0.99 (95% CI

0.73 to 1.34), tozinameran was 0.98 (95% CI 0.73 to 1.33)

and elasomeran was 1.04 (95% CI 0.71 to 1.50). Moreover,

no signal of disproportionate reporting was observed in

viral vector COVID- 19 vaccines (viral vector COVID- 19

vaccines ROR 0.69 (95% CI 0.50 to 0.96); Vaxzevria ROR

0.75 (95% CI 0.53 to 1.05) and Ad26.COV2.S ROR 0.32

(95% CI 0.15 to 0.67)) (table 2).

In the subgroup analysis of primary analysis, we did

not find an increased reporting of ILD according to age

groups, sex and region (table 3, online supplemental

table 6). The ILD following COVID- 19 vaccination was

not associated with a disproportionality signal regardless

ILD cases (N=679) Non- cases (N=6790)

P valueN (%) N (%)

Serious <0.0001

Yes 625 (92.1) 2323 (34.5)

Seriousness <0.0001

Death 116 (17.1) 287 (4.2)

Life threatening 97 (14.3) 162 (2.4)

Caused/Prolonged hospitalisation 285 (42.0) 582 (8.6)

Disabling/incapacitating 13 (1.9) 91 (1.3)

Congenital anomaly/birth defect 0 (0.0) 3 (0.0)

Other 114 (16.8) 1218 (17.9)

Region <0.0001

African 4 (0.6) 364 (5.4)

Americas 54 (8.0) 632 (9.3)

South- East Asia 6 (0.9) 121 (1.8)

European 577 (85.0) 4398 (64.8)

Eastern Mediterranean 8 (1.2) 342 (5.0)

Western Pacic 30 (4.4) 933 (13.7)

Notier type <0.0001

Physician 527 (77.6) 3675 (54.1)

Pharmacist 50 (7.4) 1055 (15.5)

Other health professional 102 (15.0) 2060 (30.3)

Time to onset (case=574, non- case=6064) 0.0077

Mean±SD 32.7±64.7 26.6±57.3

Median (Q1–Q3) 7 (1–35) 1 (0–15)

*Cancer therapy: bleomycin; gemcitabine; epidermal growth factor receptor- targeted agent (erlotinib, getinib, panitumumab, cetuximab);

mammalian target of rapamycin- inhibitor (everolimus, temsirolimus, sirolimus); immune checkpoint inhibitor (nivolumab, pembrolizumab,

avelumab, durvalumab, ipilimumab), rheumatology drugs: methotrexate; leunomide, biological disease- modifying anti- rheumatic drugs

(tumour necrosis factor) agent (iniximab, etanercept, adalimumab), tocilizumab, rituximab), anti- infection agents (nitrofurantoin, daptomycin,

interferon), cardiology drugs (amiodarone, bepridil, statin (lovastatin, simvastatin, pravastatin, atorvastatin, uvastatin, rosuvastatin,

cerivastatin)).

ICSRs, individual case safety reports.

Table 1 Continued

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of age groups (under 65 years; ROR 0.94 (95% CI 0.65

to 1.35), 65 years and older; ROR 0.70 (95% CI 0.41 to

1.17). The COVID- 19 vaccination emerged with no signal

in both males and females (males ROR 0.81 (95% CI 0.55

to 1.19), females ROR 0.93 (95% CI 0.59 to 1.46)). There

was no signal when stratifying Western Pacific region and

the other regions (ROR 0.42 (95% CI 0.16 to 1.14) and

ROR 0.88 (95% CI 0.65 to 1.21).

The results of the sensitivity analyses were similar to

those of the primary analysis (figure 3, online supple-

mental table 7). There was no disproportionality signal

when considering diverse AE definitions and potential

biases (figure 3, online supplemental table 7). The ROR

of influenza vaccines was 0.44 (95% CI 0.27 to 0.71). The

results of sensitivity analysis 7 compared with influenza

vaccines were consistent with the primary analysis (online

supplemental tables 8 and 9)

DISCUSSION

The present study aimed to identify the characteristics of

ILD following COVID- 19 vaccination and the dispropor-

tionality between COVID- 19 vaccines and ILD using the

global pharmacovigilance database. We identified 679

ILD cases from VigiBase defined using MedDRA SMQ

and performed disproportionality analysis. To the best of

our knowledge, this is the first study to investigate the

signals of disproportionate reporting of ILD associated

with COVID- 19 vaccines. Compared with other vaccines,

no significant signal of disproportional reporting of ILD

was observed for COVID- 19 vaccines. These findings were

consistent across several analyses conducted after consid-

ering potential biases. Moreover, the signal of dispropor-

tionality was not detected when compared with the influ-

enza vaccine which is known to induce ILD.

In our study, reports received from European

accounted for the majority of ILD cases (85.0%) following

COVID- 19 vaccination. In contrast to the present study,

most ILD cases following COVID- 19 vaccination have

been reported in South- East Asia, including South Korea

and Japan since Park et al reported the first ILD case

following mRNA COVID- 19 vaccination.

15 16 18–20

Kono et

al suggested that South- East Asian population should be

carefully monitored since it is at a high risk of COVID- 19

vaccine- related ILD.

Among 30 cases of ILD identified

following COVID- 19 vaccination in the Western Pacific,

which is classified as Asia by WHO, and the signal of ILD

was not detected when compared with other vaccines

(ROR 1.68, 95% CI 0.68 to 4.16) (table 2). However,

the result of subgroup analysis according to the region

should be interpreted with caution because of the small

number of cases and incomplete information on ICSRs.

Figure 2 The number of ILD cases following COVID- 19

vaccination during the study period. The brackets () present

the proportion of serious AE among ICSRs reported ILD

following COVID- 19 vaccination. AE, adverse event; ICSR,

individual case safety report; ILD, interstitial lung disease.

Table 2 Reporting OR (ROR) of COVID- 19 vaccines and all other vaccines (primary analysis)

Type of analysis ILD cases Non- cases ROR (95% CI)

Primary analysis (cases: 679, non- cases: 6790)

The other vaccines 53 (7.8) 459 (6.8) Reference

COVID- 19 vaccines 626 (92.2) 6331 (93.2) 0.86 (0.64 to 1.15)

mRNA COVID- 19 vaccines 448 (66.0) 3912 (57.6) 0.99 (0.73 to 1.34)

Tozinameran 373 (58.9) 3282 (54.4) 0.98 (0.73 to 1.33)

Elasomeran 73 (11.5) 611 (10.1) 1.04 (0.71 to 1.50)

Viral vector COVID- 19 vaccines 137 (20.2) 1718 (25.3) 0.69 (0.50 to 0.96)

Vaxzevria 126 (19.9) 1461 (24.2) 0.75 (0.53 to 1.05)

Gam- COVID- Vac 0 (0.0) 2 (0.0) NC

Ad26.COV2.S 8 (1.3) 220 (3.6) 0.32 (0.15 to 0.67)

Protein- based COVID- 19 vaccines 0 (0.0) 3 (0.0) NC

NVX- CoV2373 0 (0.0) 3 (0.1) NC

Others 41 (6.0) 698 (10.3) 0.51 (0.33 to 0.78)

ILD, interstitial lung disease; NC, not calculated.

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A previous systematic review of drug- induced ILD iden-

tified male has been as a risk factor for drug- induced

ILD, especially in those treated with amiodarone, metho-

trexate, epidermal growth factor receptor tyrosine kinase

inhibitor (EGFR- TKI) and premetrexed.

Males were

predominant in previous case reports of ILD related

to COVID- 19 vaccination.

15 16 18–20

However, this study

observed no signal of disproportionate reporting regard-

less of sex (males (ROR 0.81, 95% CI 0.55 to 1.19), females

(ROR 0.93, 95% CI, 0.59 to 1.46)) (online supplemental

table 6). Further studies are required to identify the risk

according to demographic characteristics.

We analysed the data of spontaneous reporting systems

to assess signals of AE of COVID- 19 vaccination. The

spontaneous reporting systems have several biases due

to factors that could affect reporting, which results in

incorrect signal detection. These biases can be notoriety

bias, information bias, selection bias and competition

bias.

25 32 33

We implemented different minimisation strat-

egies against these biases. First, we designed a primary

analysis to address factors that could lead to information

bias by considering to be suspected, healthcare profes-

sionals and complete information on age groups and

sex. Moreover, in sensitivity analysis 2, we used MedDRA

SMQ with narrow and broad terms. This result was in

line with the primary analysis that showed no signal of

disproportionate reporting (ROR 0.77, 95% CI 0.59 to

1.00). Second, for competition bias, it is necessary to

eliminate factors associated with vaccines/AEs of interest

(sensitivity analyses 3, 4). Results derived from sensitivity

analysis considering competition biases showed that

Table 3 Reporting OR (ROR) of COVID- 19 vaccines and all other vaccines in subgroup analysis

Type of analysis ILD cases Non- cases ROR (95% CI)

Subgroup analysis

Age

Age <65 (case=315, non- case=3150)

The other vaccines 36 (11.4) 339 (10.8) Reference

COVID- 19 vaccines 268 (85.1) 2447 (77.7) 0.94 (0.65 to 1.35)

Age ≥65 (case=364, non- case=3640)

The other vaccines 17 (4.7) 120 (3.3) Reference

COVID- 19 vaccines 347 (95.3) 3520 (96.7) 0.70 (0.41 to 1.17)

Gender

Male (case=356, non- case=3560)

The other vaccines 31 (8.7) 254 (7.1) Reference

COVID- 19 vaccines 325 (91.3) 3306 (92.9) 0.81 (0.55 to 1.19)

Female (case=323, non- case=3230)

The other vaccines 22 (6.8) 205 (6.4) Reference

COVID- 19 vaccines 301 (93.2) 3025 (93.7) 0.93 (0.59 to 1.46)

Region

Western Pacic region (case=30, non- case=933)

The other vaccines 5 (16.7) 73 (7.8) Reference

COVID- 19 vaccines 25 (83.3) 860 (92.2) 0.42 (0.16 to 1.14)

The other regions (case=649, non- case=5857)

The other vaccines 48 (7.4) 386 (6.6) Reference

COVID- 19 vaccines 601 (92.6) 5471 (93.4) 0.88 (0.65 to 1.21)

ILD, interstitial lung disease.

Figure 3 Reporting OR (ROR) of sensitivity analysis. AE,

adverse event; AESI, adverse event of special event; ICSR,

individual case safety report; ILD, interstitial lung disease;

MedDRA, medical dictionary for regulatory activities; SMQ,

standardised MedDRA queries.

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Open access

COVID- 19 vaccines had no disproportionality signal of

ILD compared with the other vaccines (ROR 1.02, 95%

CI 0.73 to 1.42 and ROR 0.96, 95% CI, 0.69 to 1.33,

respectively). Third, in pharmacovigilance, temporal

bias (the Weber effect or notoriety bias) refers to varia-

tion in the number of reports after a specific event, such

as safety alerts and market authorisation. The signal of

ILD was not observed when minimising temporal biases;

the RORs of sensitivity analyses 5 and 6 were 0.72 (95%

CI 0.52 to 0.98) and 0.75 (95% CI 0.38 to 1.48), respec-

tively. Fourth, we defined reference groups that received

influenza and other vaccines instead of all other drugs

to avoid selection bias. The analysis using influenza

vaccines as a positive control in the secondary analysis

showed that COVID- 19 vaccines emerged with no signal

when compared with influenza vaccines (ROR 0.44, 95%

CI 0.27 to 0.71). However, the risk–benefits of COVID- 19

vaccines should be carefully assessed.

The mechanisms of COVID- 19 vaccine- induced ILD

are unclear. To date, both cytotoxicity and immune-

mediated lung injury are considered as main mecha-

nisms that initiate drug- induced ILD. Although it is rare,

the event can be fatal and patients might require hospi-

talisation.

According to previous reports, the influenza

vaccination can induce ILD by increasing the levels of

inflammatory cytokines.

Several cases of COVID- 19

mRNA vaccine associated ILD have been reported.

15–21

Given the similar clinical characteristics with influenza

vaccine- induced ILD, including onset time, chest CT

findings and responsiveness to corticosteroids, it can

be speculated that ILD following COVID- 19 vaccina-

tion might also be due to immune- mediated pulmonary

injury. These studies suggest that COVID- 19 vaccination

induces immune- mediated injury to the lungs through

T- cells, which adopt a predominant type one phenotype

in susceptible patients.

17–21 35

However, further studies

with a large number of ILD patients who received the

COVID- 19 vaccines are needed.

12 15

This study has several limitations. First, selective

reporting of AEs might have been compromised in the

spontaneous reporting database although we strived to

minimise biases. During the pandemic, the number of

ICSRs following COVID- 19 vaccination increased rapidly,

which might have resulted in differential reporting

rates and influenced parameters. We applied 1:10 exact

matching to reduce the imbalance between case and

non- case and performed various analyses. The results

of our study did not provide exhaustivity of COVID- 19

vaccine- induced ILD although it suggests focusing on the

risk. Second, we analysed ICSRs without causality assess-

ment. However, VigiBase contains essential information

required for causality assessment, including age, sex,

primary reporter and time- to- onset. Third, concerns on

the validity of ILD in spontaneous reporting database

might be raised. To overcome this limitation, we restricted

physicians (77.6%), pharmacists (7.4%) and other health

professionals (14.8%) as notifier types and defined ILD

using MedDRA SMQs, which are validated by expert

discussion. Fourth, in the present study, the majority

of ILD cases following vaccination were predominantly

in the European population, which may introduce bias

due to population heterogeneity. Fifth, previous studies

have suggested that COVID- 19 infection can lead to the

occurrence or exacerbation of ILD, referred to as post-

COVID- 19 ILD. Notably, the VigiBase we used cannot

ascertain the COVID- 19 infection status. Therefore,

the study findings should be interpreted with caution.

Finally, this study did not assess the risk of specific molec-

ular components of vaccines. The excipients such as adju-

vants, stabilisers, preservatives and trace components can

cause AE following immunisation. Therefore, besides

vaccines, the safety of excipients should also be evalu-

ated. Despite these limitations, our study used a global

pharmacovigilance database with over 30 million ICSRs

and could offer additional hypotheses for AEs. In addi-

tion, the case/non- case approach allowed us to study rare

AEs and could represent the use of drugs in real world

settings.

Since there were no population- based studies

and previous case reports have included exacerbation of

pre- existing ILD with death, additional safety studies are

needed.

CONCLUSION

In conclusion, we identified no significant dispropor-

tionality signal of ILD associated with COVID- 19 vaccines

using global pharmacovigilance database. This finding is

consistent regardless of the subpopulation. Furthermore,

the disproportional analysis compared with the influenza

vaccines that are known to cause ILD emerged with no

signal. However, serious AE accounted for the majority

of ILD cases following COVID- 19 vaccination and events,

including hospitalisations, have been reported. We

suggest careful monitoring of COVID- 19 vaccine- induced

ILD. This study may provide information that can be

useful for making decisions on subsequence COVID- 19

vaccine strategies. However, further studies using patient-

level information such as disease history and diagnostic

test results are required for more conclusive evidence.

Author afliations

College of Pharmacy, Chung- Ang University, Seoul, Korea

Department of Global Innovative Drugs, The Graduate School of Chung- Ang

University, Seoul, Korea

Division of Pulmonary and Allergy Medicine, Department of Internal

Medicine, Chung- Ang University Gwangmyeong Hospital, Gwangmyeong- si,

Gyeonggi- do, Korea

Department of Internal Medicine, Chung- Ang University College of Medicine,

Seoul, South Korea

Division of Pulmonary and Allergy Medicine, Department of Internal

Medicine, Chung- Ang University Hospital, Seoul, Korea

Contributors M- TL and S- YJ participated in the conception and design of study.

M- TL and S- YJ participated in the data acquisition and data analysis. M- TL, JWL,

JCC, K- MG and S- YJ participated in the data interpretation. M- TL participated

in the draft of the manuscript. JWL, HJL, J- ML, JCC and K- MG helped to revise

the manuscript for intellectual content. All authors read and approved the nal

manuscript. S- YJ is reponsible for the overall content as guarantor.

Funding This research, and the journal’s Rapid Service Fee, was supported

by Government wide R&D Fund Project for Infectious Disease Research

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(GFID) by Republic of Korea (grant number: HG18C0066). This research was

supported by Basic Science Research Program through the National Research

Foundation of Korea (NRF) funded by the Ministry of Education (grant number

2021R1A6A1A03044296).

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in

the design, or conduct, or reporting, or dissemination plans of this research.

Patient consent for publication Not applicable.

Ethics approval This study was conducted in accordance with the Declaration

of Helsinki. The study protocol was approved for exemption from review by the

Institutional Review Board of Chung- Ang University (IRB number: 1041078- 201903-

HR- 071- 01), because this study analyaed a secondary database. Informed consent

from subjects was waived due to the database containing anonymised data that

cannot identify study subjects.

Provenance and peer review Not commissioned; externally peer reviewed.

Data availability statement Data may be obtained from a third party and are not

publicly available. The data analysed in this study are available from VigiBase upon

formal request to the Uppsala Monitoring Centre at the WHO Collaborating Centre

for International Drug Monitoring.

Supplemental material This content has been supplied by the author(s). It has

not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been

peer- reviewed. Any opinions or recommendations discussed are solely those

of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and

responsibility arising from any reliance placed on the content. Where the content

includes any translated material, BMJ does not warrant the accuracy and reliability

of the translations (including but not limited to local regulations, clinical guidelines,

terminology, drug names and drug dosages), and is not responsible for any error

and/or omissions arising from translation and adaptation or otherwise.

Open access This is an open access article distributed in accordance with the

Creative Commons Attribution Non Commercial (CC BY- NC 4.0) license, which

permits others to distribute, remix, adapt, build upon this work non- commercially,

and license their derivative works on different terms, provided the original work is

properly cited, appropriate credit is given, any changes made indicated, and the

use is non- commercial. See:http://creativecommons.org/licenses/by-nc/4.0/.

ORCID iD

Sun- YoungJung http://orcid.org/0000-0003-2032-112X

REFERENCES

1 WHO Coronavirus (COVID- 19) dashboard. n.d. Available: https://

covid19.who.int/2023

2 Savinkina A, Bilinski A, Fitzpatrick M, etal. Estimating deaths

averted and cost per life saved by scaling up mRNA COVID- 19

vaccination in low- income and lower- middle- income countries in

the COVID- 19 Omicron variant era: a modelling study. BMJ Open

2022;12:e061752.

3 World Health Organization. From emergency response to long- term

COVID- 19 disease management. 2023: 14.

4 FDA. FDA Brieng Document Future Vaccination Regimens

Addressing COVID- 19. 2023.

5 Kozlov M. Should COVID vaccines be given yearly? Proposal divides

US scientists. Nature 2023. 10.1038/d41586-023-00234-7 [Epub

ahead of print 27 Jan 2023].

6 Huapaya JA, Wilfong EM, Harden CT, etal. Risk factors for mortality

and mortality rates in interstitial lung disease patients in the intensive

care unit. Eur Respir Rev 2018;27:180061.

7 Aronson KI, Danoff SK, Russell A- M, etal. Patient- centered

outcomes research in interstitial lung disease: an ofcial American

Thoracic Society research statement. Am J Respir Crit Care Med

2021;204:e3–23.

8 Wijsenbeek M, Suzuki A, Maher TM. Interstitial lung diseases. Lancet

2022;400:769–86.

9 Olson AL, Hartmann N, Patnaik P, etal. Healthcare resource

utilization and related costs in chronic brosing interstitial lung

diseases with a progressive phenotype: a US claims database

analysis. Adv Ther 2022;39:1794–809.

10 Schwaiblmair M, Behr W, Haeckel T, etal. Drug induced interstitial

lung disease. Open Respir Med J 2012;6:63–74.

11 Spagnolo P, Bonniaud P, Rossi G, etal. Drug- induced interstitial lung

disease. Eur Respir J 2022;60:2102776.

12 Watanabe S, Waseda Y, Takato H, etal. Inuenza vaccine- induced

interstitial lung disease. Eur Respir J 2013;41:474–7.

13 DeDent AM, Farrand E. Vaccine- induced interstitial lung disease: a

rare reaction to COVID- 19 vaccination. Thorax 2022;77:9–10.

14 Okusaki T, Fukuhara K. Exacerbation of connective tissue disease-

associated interstitial lung disease due to inuenza vaccination.

Respir Med Case Rep 2021;33:101463.

15 Park JY, Kim J- H, Lee IJ, etal. COVID- 19 vaccine- related interstitial

lung disease: a case study. Thorax 2022;77:102–4.

16 Kono A, Yoshioka R, Hawke P, etal. Correction to: a case of

severe interstitial lung disease after COVID- 19 vaccination. QJM

2022;115:hcac066.

17 Sgalla G, Magrì T, Lerede M, etal. COVID- 19 vaccine in patients with

exacerbation of idiopathic pulmonary brosis. Am J Respir Crit Care

Med 2022;206:219–21.

18 Matsuzaki S, Kamiya H, Inoshima I, etal. COVID- 19 mRNA vaccine-

induced pneumonitis. Intern Med 2022;61:81–6.

19 So C, Izumi S, Ishida A, etal. COVID- 19 mRNA vaccine- related

interstitial lung disease: two case reports and literature review.

Respirol Case Rep 2022;10:e0938.

20 Yoshifuji A, Ishioka K, Masuzawa Y, etal. COVID- 19 vaccine induced

interstitial lung disease. J Infect Chemother 2022;28:95–8.

21 Ehteshami- Afshar S, Raj R. COVID- 19 mRNA vaccines and

interstitial lung disease exacerbation: causation or just a temporal

association Am J Respir Crit Care Med 2022;206:919.

22 Yoo H, Kim SY, Park MS, etal. COVID- 19 vaccine- associated

Pneumonitis in the Republic of Korea: a nationwide multicenter

survey. J Korean Med Sci 2023;38:e106.

23 Vigibase WHO- UMC 2023. n.d. Available: https://who-umc.org/

vigibase/

24 Smadja DM, Yue Q- Y, Chocron R, etal. Vaccination against

COVID- 19: insight from arterial and venous thrombosis occurrence

using data from VigiBase. Eur Respir J 2021;58:2100956.

25 Faillie JL. Case- non- case studies: principle, methods, bias and

interpretation. Therapies 2019;74:225–32.

26 Montastruc J- L, Sommet A, Bagheri H, etal. Benets and strengths

of the disproportionality analysis for identication of adverse drug

reactions in a pharmacovigilance database. Br J Clin Pharmacol

2011;72:905–8.

27 Noguchi Y, Tachi T, Teramachi H. Detection algorithms and attentive

points of safety signal using spontaneous reporting systems as a

clinical data source. Brief Bioinform 2021;22:bbab347.

28 Pariente A, Didailler M, Avillach P, etal. A potential competition

bias in the detection of safety signals from spontaneous reporting

databases. Pharmacoepidemiol Drug Saf 2010;19:1166–71.

29 Law B, Sturkenboom MD. 2.3.1 tier 1 AESI: ICD- 9/10- CM and

Meddra codes. 2017.

30 Kono A, Hawke P, Yoshioka R. Response to: Multisystem

inammatory syndrome following COVID- 19 vaccination: ignored

and underdiagnosed. QJM 2022;115:698.

31 Skeoch S, Weatherley N, Swift AJ, etal. Drug- induced interstitial

lung disease: a systematic review. J Clin Med 2018;7:356.

32 Raschi E, Poluzzi E, Salvo F, etal. Pharmacovigilance of sodium-

glucose co- transporter- 2 inhibitors: what a clinician should know on

disproportionality analysis of spontaneous reporting systems. Nutr

Metab Cardiovasc Dis 2018;28:533–42.

33 Raschi E, Fusaroli M, Diemberger I, etal. Direct oral anticoagulants

and interstitial lung disease: emerging clues from pharmacovigilance.

Drug Saf 2020;43:1191–4.

34 Matsuno O. Drug- induced interstitial lung disease: mechanisms and

best diagnostic approaches. Respir Res 2012;13:39.

35 Keech C, Albert G, Cho I, etal. Phase 1–2 trial of a SARS- CoV-2

recombinant spike protein nanoparticle vaccine. N Engl J Med

2020;383:2320–32.

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