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Original Article
Risk and outcomes of coronavirus disease
(COVID-19) in patients with inflammatory
bowel disease: a systematic review and
meta-analysis
Anupam Kumar Singh
1
, Anuraag Jena
1
, Praveen Kumar-M
2
,
Vishal Sharma
1#
and Shaji Sebastian
3,#
Abstract
Background: The risk of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infection and
clinical outcomes of coronavirus disease (COVID-19) in inflammatory bowel disease are unclear.
Methods: We searched PubMed and Embase with the keywords: inflammatory bowel disease, Crohn’s disease,
ulcerative colitis and COVID-19, novel coronavirus and SARS-CoV-2. We included studies reporting the frequency of
COVID-19 infection and outcomes (hospitalisation, need for intensive care unit care and mortality) in patients with
inflammatory bowel disease. We estimated the pooled incidence of COVID-19 in inflammatory bowel disease and
comparative risk vis-a-vis the general population. We also estimated the pooled frequency of outcomes and com-
pared them in patients who received and did not receive drugs for inflammatory bowel disease.
Results: Twenty-four studies were included. The pooled incidence rate of COVID-19 per 1000 patients of inflam-
matory bowel disease and the general population were 4.02 (95% confidence interval (CI) 1.44–11.17) and 6.59
(3.25–13.35), respectively, with no increase in relative risk (0.47, 0.18–1.26) in inflammatory bowel disease. The
relative risk of the acquisition of COVID-19 was not different between ulcerative colitis and Crohn’s disease (1.03,
0.62–1.71). The pooled proportion of COVID-19-positive inflammatory bowel disease patients requiring hospital-
isation and intensive care unit care was 27.29% and 5.33% while pooled mortality was 4.27%. The risk of adverse
outcomes was higher in ulcerative colitis compared to Crohn’s disease. The relative risks of hospitalisation, inten-
sive care unit admission and mortality were lower for patients on biological agents (0.34, 0.19–0.61; 0.49, 0.33–0.72
and 0.22, 0.13–0.38, respectively) but higher with steroids (1.99, 1.64–2.40; 3.41, 2.28–5.11 and 2.70, 1.61–4.55) or 5-
aminosalicylate (1.59, 1.39–1.82; 2.38, 1.26–4.48 and 2.62, 1.67–4.11) use.
Conclusion: SARS-CoV-2 infection risk in patients with inflammatory bowel disease is comparable to the general
population. Outcomes of COVID-19-positive inflammatory bowel disease patients are worse in ulcerative colitis,
those on steroids or 5-aminosalicylates but outcomes are better with biological agents.
Keywords
Ulcerative colitis, Crohn’s disease, SARS-CoV-2, coronavirus
Received: 26 August 2020; accepted: 14 October 2020
1
Department of Gastroenterology, Postgraduate Institute of Medical
Education and Research, Chandigarh, India
2
Department of Pharmacology, Postgraduate Institute of Medical
Education and Research, Chandigarh, India
3
Hull University Teaching Hospitals NHS Trust, Hull, UK
#
The last two authors are co-senior authors for the paper
Corresponding authors:
Vishal Sharma, Department of Gastroenterology, Postgraduate
Institute of Medical Education and Research, Chandigarh, India.
Emails: docvishalsharma@gmail.com; sharma.vishal@pgimer.edu.in
United European Gastroenterology
Journal
0(0) 1–20
!Author(s) 2020
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/2050640620972602
journals.sagepub.com/home/ueg
Current knowledge
•Inflammatory bowel disease may be associated with an increased risk of various infections.
•Certain inflammatory bowel disease therapies may predispose to an increased risk of infections (e.g. anti-
tumour necrosis factor and tuberculosis, tofacitinib and herpes zoster).
•The effect of inflammatory bowel disease and inflammatory bowel disease therapies on coronavirus disease
infection and outcomes is unclear.
What are the new findings
•In this meta-analysis, we found that the risk of coronavirus disease in patients with inflammatory bowel
disease is similar to the general population.
•The risk of coronavirus disease does not seem to be affected by the underlying type of inflammatory bowel
disease, that is, Crohn’s disease or ulcerative colitis.
•The risk of adverse outcomes in inflammatory bowel disease is more in patients receiving steroids and 5-
aminosalicylates.
•Biological agent use seems to be protective against adverse outcomes of coronavirus disease in inflammatory
bowel disease patients.
Introduction
The coronavirus disease (COVID-19) pandemic has
brought forth a multitude of challenges for patients
having inflammatory bowel disease (IBD) and health-
care practitioners involved in the care of patients with
IBD. IBDs, both ulcerative colitis (UC) and Crohn’s
disease (CD), are associated with an increased risk of
infections, especially in elderly patients, active IBD and
those on immunosuppressive medications.
1
In many
regions, national-wide lockdowns have had effects on
the availability of drugs and access to healthcare. To
add to this, patients have faced psychological problems
such as anxiety because of the concerns about their
health in the presence of underlying IBD and ongoing
treatment with immunosuppressive drugs.
2
While
COVID-19 has high infectivity and carries the risk of
significant morbidity and mortality, information on the
risk of infection by severe acute respiratory syndrome-
related coronavirus 2 (SARS-CoV-2) in IBD patients
and the outcomes is limited.
Angiotensin-converting enzyme 2 (ACE-2) receptor,
which has a role in viral entry into host cells, is
expressed in the human intestine and the expression
could be upregulated after infection with SARS-
CoV-2. There are conflicting data on changes in the
expression of ACE-2 in ileal and colonic mucosa of
patients with active IBD.
3,4
In addition, the therapeutic
agents used in IBD could affect ACE-2 expression.
4
Therefore, a complex interplay of receptors, physiolog-
ical processes and therapies may define the risk of
acquisition and clinical outcomes in these patients.
Furthermore, published evidence regarding the risk
of the acquisition of coronaviruses and clinical out-
comes in infected patients with IBD was unavailable
prior to this pandemic. Various organisations, in this
state of evidence vacuum, have provided expert
consensus-based guidance for clinicians and patients
with IBD.
5
The published literature on IBD and
COVID-19 is limited by cohort studies and case series
including a small number of patients. This makes it
difficult to assess the actual risk of COVID-19 infection
in patients with IBD and the consequences of such an
infection. Another important concern is the effect of
various therapeutic agents used in IBD on the risk of
acquisition and the clinical course of COVID-19.
Therefore, we planned to do a systematic review of
observational studies on the risk of the acquisition of
SARS-CoV-2 in patients with IBD, and to estimate
whether the drugs affect the risk of acquisition and
outcomes of SARS-CoV-2 infection.
Methods
This meta-analysis was conducted in accordance with
the Meta-analysis Of Observational Studies in
Epidemiology (MOOSE) guidance and Preferred
Reporting Items for Systematic Reviews and Meta-
Analyses (PRISMA) guidance.
Database search
We searched electronic databases using PubMed and
Embase from 1 December 2019 to 29 July 2020. The
keywords used for the search were inflammatory bowel
disease, ulcerative colitis, Crohn disease, Crohn’s dis-
ease combined using the operator ‘AND’ Coronavirus,
COVID-19, SARS-COV-2, nCOV, coronaviridae
infection or coronavirus disease 2019 (detailed strategy
as described in Supplementary Table1). The bibliogra-
phies of included studies and reviews were searched for
additional eligible studies. The authors of unpublished
2United European Gastroenterology Journal 0(0)
data of which we were aware were contacted for data.
The eligible titles were combined and the duplicates
were removed. The titles and abstracts were then
reviewed by two reviewers (AKS and AJ). After screen-
ing of the titles and abstracts, papers were selected for
full text screening. Differences, if any, were resolved
after discussion with a third reviewer (VS).
Inclusion and exclusion criteria
We included all relevant articles which fulfilled the
inclusion criteria irrespective of the type (original
paper, abstract, letter, correspondence), format or the
language of publication. We included studies which
reported at least one of the two key outcomes:
(a) risk or frequency of acquisition of SARS-CoV-2
infection in IBD patients with or without comparison
to the general population; or (b) outcomes (hospital-
isation, need for intensive care unit (ICU) care or mor-
tality) in IBD patients infected with SARS-COV-2. We
excluded studies which did not have relevant outcome
data or the data were incomplete. We also excluded
single patient case reports, reviews, editorial and
commentaries.
Data collection
Data were extracted from the included studies by the
two reviewers (AKS and AJ) and any discrepancy was
resolved by discussion with the third reviewer (VS).
Extracted data included publication details (author
and year), place of study, overall population of IBD
patients and COVID-19-positive IBD patients, age,
gender, disease type (CD or UC), presence of comor-
bidities, current treatment including 5-aminosalicylic
acid (5-ASA), immunomodulators (thiopurines, calci-
neurin inhibitors and methotrexate), steroids, biologi-
cal agents (anti-tumour necrosis factor (TNF),
vedolizumab, ustekinumab) and small molecule inhib-
itors and details of their outcomes (hospitalisation,
need for ICU and mortality). The definitions of
COVID-19 infection used in various studies were also
recorded.
Data analysis
The analysis was conducted using R statistical software
version 4.0.1 and meta package was used additionally.
The inverse variance method with a random effect
approach was used for computing the pooled summary
of incidence. The incidence was logit transformed for
computing summary and the Clopper–Pearson confi-
dence interval was used for individual studies.
Similarly, the overall risk ratio was computed by the
inverse variance method with a random effect
approach. Continuity correction of 0.5 was applied
for cells with 0 value. The heterogeneity was deter-
mined by I
2
and Pvalue of heterogeneity. The
DerSimonian–Laird estimator was used for computing
the tau.
2
We used a random effect approach irrespec-
tive of I
2
considering that heterogeneity was present
among the studies at the level of study design and
approach towards the research question.
We calculated the pooled incidence of COVID-19
infection in patients with IBD and in the general pop-
ulation. We calculated the pooled risk ratio of acquisi-
tion of COVID-19 in IBD as compared to the general
population. Among the IBD population, the risk of
acquiring the COVID-19 infection was assessed for
the subtype of IBD; that is, UC and CD. We also did
subgroup analysis for assessing the impact of the age of
patients on the incidence of COVID-19 in IBD patients
based on a cut-off of 45 years. We also calculated the
risk of infection in IBD patients based on the medica-
tion used for the treatment of IBD (5-ASA, immuno-
modulators, steroids and biological agents (anti-TNF,
vedolizumab, ustekinumab)) at the time of acquiring
the COVID-19 infection. For the purpose of analysis,
the thiopurines, calcineurin inhibitors and antimetabo-
lites (methotrexate) were grouped together as
immunomodulators.
We estimated the pooled frequency of various out-
comes of interest: hospitalisation, need for ICU care
and mortality in the patients with IBD infected with
COVID-19 and similarly for the subtypes of IBD (UC
and CD) and the pooled risk of each outcome in
patients receiving or not receiving various medications
used for the treatment of IBD (5-ASA, immunomodu-
lators, steroids and biological agents). In the outcome
analysis, the biological agents (anti-TNF, vedolizumab
and ustekinumab) were clubbed together as ‘biologics’.
The risk ratio was calculated for hospitalisation, need
for ICU and mortality in patients with UC and CD
infected with COVID-19. For the outcomes which
were found to be heterogeneous (I
2
>50%), assessment
of heterogeneity by the Baujat plot and leave-one-out
analysis was done.
Methodological quality and risk of bias
assessment
Two of the investigators (AKS and AJ) independently
assessed the methodological quality and risk of bias for
each study. We used the Joanna Briggs Institute critical
appraisal checklist for studies reporting the incidence
and outcome data.
6,7
The Joanna Briggs appraisal for
incidence data includes questions about the appropri-
ateness of study sample and selection, description of
setting and subjects, completeness of provided data
and analysis, and the appropriateness of measuring
the condition. For outcome data, the Joanna Briggs
Singh et al. 3
appraisal for case series includes questions about inclu-
sion, standard and similar methods of diagnosing the
condition and consecutiveness and completeness of
participant data and outcomes. Any discordance in
quality assessment was resolved by mutual agreement
of both the investigators (AKS and AJ) in discussion
with a third reviewer (VS).
Results
After the database search a total of 390 titles were
identified and two additional papers were identified
from other sources. In all there were 157 duplicates.
Therefore, a total of 235 articles were screened for
title and abstract and 35 papers underwent full text
screening (Figure 1). Eventually, data from 24 studies
were used for analysis. This also includes data
extracted from the SECURE-IBD registry (on 29 July
2020) and one study identified by manual search.
Table 1 provides the details of the included studies
including location, number of subjects, age, basis of
diagnosis, comorbidities and the eventual inclusion in
one of the two analyses.
2,8–29
The definitions used for
COVID diagnosis were based on real time polymerase
chain reaction (RT-PCR) testing or clinical symptoms
consistent with COVID-19 with radiological evidence
of pneumonia in most studies (Table 1). Supplementary
Table 2 lists the reasons for the exclusion of studies.
Risk of COVID-19 in IBD patients
Seventeen studies provided the information on the inci-
dence rate of COVID-19 in IBD. The pooled incidence
rate of COVID-19 in patients with IBD was 4.02 (95%
confidence interval (CI) 1.44–11.17; I
2
¼98%) per 1000
population (Figure 2). The corresponding rate of infec-
tion as reported in the general population was 6.59
(3.25–13.35; I
2
¼100%) in the six participating studies
(Figure 2). The pooled relative risk (RR) of the acqui-
sition of COVID-19 in patients with IBD was not dif-
ferent from the general population (0.47, 0.18–1.26;
I
2
¼89%, Figure 2). For studies in which the mean/
median age of IBD patients was provided, we
calculated the pooled incidence of COVID separately
for studies with a mean/median age of 45 years or less
and over 45 years. While the pooled incidence in studies
with a mean/median age of 45 years or less was 2.06%
(0.77–5.54; I
2
¼18), it was 4.44% (0.99–19.61; I
2
¼96%)
for the studies with an age over 45 years
(Supplementary Figure 1). In addition, the studies
which provided information on the impact of age on
COVID-19 infection in IBD are shown in
Supplementary Table 3.
The overall incidence of COVID-19 in patients with
UC was 4.55 (0.76–26.80; I
2
¼93%) per 1000 cases
(Supplementary Figure 2). The overall incidence rate
of COVID-19 in patients with CD was 6.66 (1.49-
29.35; I
2
¼92%) per 1000 cases (Supplementary
Total records: 392
Duplicates removed: 157
Identification
Screening
Eligibility
Included
Records screened: 235
Full text assessed for eligibilty: 35
Studies included in quantitative
synthesis (meta-analysis) : 24
Records excluded on the
title and abstract
Case report: 26
Comment/editorial/letter: 36
Review: 24
Unrelated: 114
Records excluded after full text
assessment with reasons
No relevant information: 10
Duplication of data: 1
Records identified through
database searching
Pubmed: 194
Embase: 196
Additional records identified
through other sources: 2
Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart showing selection process of
the studies.
4United European Gastroenterology Journal 0(0)
Table 1. Summary of various included studies, patient characteristics and the data provided for analysis.
Study Location No. of total IBD
No. of COVID IBD
and basis of
diagnosis
Male:
female Age (years) Comorbid conditions UC and CD Drugs Outcome
Data used for analysis
Risk of
COVID-19
Outcome of
COVID-19
Taxonera C Madrid, Spain 1918 12
RT PCR
1:3 52 16 Comorbidities 5
(41.6%)
Hypertension 3
(25%)
DM 2 (16.7%)
CKD 1 (8.3%)
CLD 1 (8.3%)
CV disease 1 (8.3%)
UC 5
CD 7
ASA 4 (33.3%)
Steroid 0
IMM 6 (50%)
Biologicals 5
(41.6%)
Anti-TNF 3 (25%)
Hosp 8 (66.7%)
ICU 1 (8.3%)
Death 2 (16.7%)
Yes Yes
Hormati A Qom, Iran 150 8
RT PCR
NA NA NA NA NA NA Yes No
Lukin DJ New York USA 119 as a cohort;
additional 80
cases as part
of case–con-
trol design
29
(9 RT PCR posi-
tive and 20
highly
suspected)
1:1.42 NA NA UC 14
CD 15
ASA 11 (37.9%)
Steroid 19
(65.5%)
IMM 2 (6.9%)
Biologics 21
(72.4%)
NA Yes No
Rodriguez- Lago I Basque country
(Spain)
NA 40
RT PCR
3:2 59
(48–68)
Comorbidities 25
(62.5%)
UC 27
CD 13
ASA 26 (65%)
Steroid 4 (10%)
IMM 13 (32.5%)
Biologicals 9
(22.5%)
Anti-TNF 4 (10%)
Hosp 21 (52.5%)
ICU 0
Death 2 (5%)
No Yes
Haberman R New York
USA
NA 37 NA NA NA UC 17
CD 20
ASA 7 (18.9%)
Steroid 1 (2.7%)
IMM 1 (2.7%)
Biologicals 24
(64.8%)
Anti-TNF 19
(51.3%)
Hosp 4 (10.8%)
ICU 0
No Yes
Turner D China
(paediatric)
1431 0
(suspected or
confirmed)
NA NA NA NA NA NA No @
Turner D South Korea
(paediatric)
272 0 NA NA NA NA NA NA No @
(continued)
Table 1. Continued.
Study Location No. of total IBD
No. of COVID IBD
and basis of
diagnosis
Male:
female Age (years) Comorbid conditions UC and CD Drugs Outcome
Data used for analysis
Risk of
COVID-19
Outcome of
COVID-19
Axelrad JE New York, USA NA 83
(confirmed or
highly
suspected)
1.13:1 35 (27–45) Asthma/COPD-10
(12%)
Hypertension 3
(3.6%)
DM 1 (1.2%)
CKD 1 (1.2%)
Malignancy 1 (1.2%)
Post-transplant 2
(2.4%)
UC 27
CD 56
ASA 13 (15.6%)
Steroid 10 (12%)
IMM 6 (7.2%)
Biologicals 58
(69.8%)
Anti-TNF 44 (53%)
Hosp 5 (6.0%)
Death 1 (1.2%)
No Yes
Khan N Nation- wide
Veteran
Cohort, USA
37857 36
ICD code based
NA 60.9 17.1 NA NA IMM 2 (5.5%)
Anti-TNF 3 (8.3%)
NA Yes No
Mosli M Saudi Arabia 1156 6
Testing
1:1 NA Comorbidities 0 UC 1
CD 5
ASA 3 (50%)
Steroid 1 (16.7%)
IMM 1 (16.7%)
Biologicals 2
(33.3%)
Anti-TNF 2
(33.3%)
NA Yes No
Scaldaferri F Italy 1451 5
? Basis
NA NA NA NA NA Hosp 0
ICU 0
Death 0
Yes Yes
Allocca M Italy and France 6000 15 1:2.75 38.4 10.54 Comorbidities 9
(60%)
Musculoskeletal
disease 3 (20%)
Hypertension 1
(6.6%)
DM 1 (6.6%)
PSC 1 (6.6%)
CV disease 1 (6.6%)
Obesity- 1
Post-transplant 1
(6.6%)
Others 1 (6.6%)
UC 6
CD 9
ASA 1 (6.6%)
Steroid 2 (13.3%)
IMM 3 (20%)
Biologicals 12
(80%)
Anti-TNF
8 (53.3%)
Hosp 5 (33.3%)
ICU 0
Death 0
Yes Yes
Grunert PC Germany 415 0 NA NA NA NA NA NA Yes No
Marafini I Italy 672 3
(RT PCR)
NA NA NA NA NA Hosp 2 (66.6%)
Death 1 (33.3%)
Yes Yes
(continued)
Table 1. Continued.
Study Location No. of total IBD
No. of COVID IBD
and basis of
diagnosis
Male:
female Age (years) Comorbid conditions UC and CD Drugs Outcome
Data used for analysis
Risk of
COVID-19
Outcome of
COVID-19
Bezzio C Italy NA 79
(RT PCR in 49 OR
clinical plus
radiology in
30)
1.26:1 45 (18–80) Comorbidities 30
(37.9%)
Hypertension 9
(11.4%)
COPD/asthma 5
(6.3%)
CV disease 5 (6.3%)
Musculoskeletal
disease 4 (5%)
Others 7 (8.8%)
UC 47
CD 32
ASA 24 (30%)
Steroid 9 (11.3%)
IMM 7 (8.8%)
Biologicals 47
(59.5%)
Anti-TNF 29
(36.7%)
Hosp 22 (27.9%)
Death 6 (7.6%)
No Yes
Yu M China, Wuhan 102 0 NA NA NA NA NA NA Yes No
An P Wuhan, China 318 0 NA NA NA NA NA NA Yes No
Singh S Multicentre, USA 196,403 232 (RT PCR or
ICD code
based)
1:1.25 51.2 18.1 Hypertension 121
(52.1%)
DM 62 (26.7%)
CKD 38 (16.3%)
CV disease 86 (37%)
CVA 30 (12.9%)
COPD/asthma 91
(39.2%)
UC 131
CD 101
NA Hosp 56 (24.1%) Yes Yes
Gubatan J North California,
USA
168 5
(RT PCR)
2:3 70.6 (4.2) Hypertension 4 (80%)
DM 2 (40%)
UC 3
CD 2
ASA 4 (80%)
Steroid 1 (20%)
IMM 1 (20%)
Biologicals 1
(20%)
Anti-TNF 1 (20%)
ICU 1 (20%)
Death 1 (20%)
Yes Yes
Norsa L Northern Italy 522 0 NA NA NA NA NA NA Yes No
Mak JWY Hong Kong
cohort
2954 0 NA NA NA NA NA NA Yes No
Mak JWY Taiwan cohort 3091 0 NA NA NA NA NA NA Yes No
Foteinogiannopoulou Greece 78 0 NA NA NA NA NA NA Yes No
(continued)
Table 1. Continued.
Study Location No. of total IBD
No. of COVID IBD
and basis of
diagnosis
Male:
female Age (years) Comorbid conditions UC and CD Drugs Outcome
Data used for analysis
Risk of
COVID-19
Outcome of
COVID-19
Gonzalez HA* Multicentre (Italy,
Spain, UK)
NA 147
(RT PCR in 61,
rest with con-
sistent
symptoms)
NA NA Comorbidities 45
(30.6%)
Hypertension 18
(12.2%)
COPD/asthma 14
(9.5%)
DM 10 (6.8%)
Obesity 11 (7.4%)
CLD 4 (2.7%)
CKD 2 (1.3%)
CV disease 8 (5.4%)
CVA 4 (2.7%)
Malignancy 1
(0.7%)
UC 65
CD 82
ASA 41 (27.8%)
Steroid 12 (8.1%)
IMM 71 (48.2%)
Biologicals 96
(65.3%)
Anti-TNF 39
(26.5%)
Hosp 44 (29.9%)
ICU 10 (6.8%)
Death 2 (1.4%)
No Yes
Grassia Italy 251 1
(not given)
NA NA NA NA NA NA Yes No
SECURE IBD Multicentre,
multi- country
registry
NA 1830 NA NA Comorbidities 669
(36.5%)
UC 812
CD 1010
Unknown 8
ASA/sulfasalazine
572 (31.2%)
Steroids 197
(10.7%)
IMM 360 (19.6%)
Biologicals 1053
(57.5%)
Anti-TNF 536
(29.2%)
Hosp 512 (27.9%)
ICU 99 (5.4%)
Death 63 (3.4%)
No Yes
IBD: inflammatory bowel disease; COVID: coronavirus disease; UC: ulcerative colitis; CD: Crohn’s disease; RT PCR: real time polymerase chain reaction; ASA: aminosalicylates; IMM: immunomodulators; Anti-TNF:
anti-tumour necrosis factor agents; ICU: intensive care unit; NA: not applicable; Hosp: hospitalisation.
@Provides a case series of seven paediatric IBD-COVID positive cases used in outcomes analysis.
*Unpublished.
Study
Total (95% CI)
Heterogeneity: Tau2 = 1.1859; Chi2 = 54.42, df = 6 (P < 0.01); I2 = 89%
Gubatan J et al
Mak JWY et al (1)
Mak JWY et al (2)
Marafini I et al
Norsa L et al
Singh S et al
Taxonera C et al
Events
5
0
0
3
0
232
12
Total
205728
168
2954
3091
672
522
196403
1918
IBD
Events
1155
1017
429
205463
6471
19776
43877
Total
108245217
14067
75210
60956
60317000
1114590
40000000
6663394
Gen. Population
Weight
100.0%
18.3%
7.9%
7.9%
16.7%
7.9%
21.3%
19.9%
IV, Random, 95% CI
0.47 [0.18; 1.26]
0.36 [0.15; 0.86]
0.01 [0.00; 0.20]
0.02 [0.00; 0.37]
1.31 [0.42; 4.05]
0.16 [0.01; 2.63]
2.39 [2.10; 2.72]
0.95 [0.54; 1.67]
Risk Ratio
0.001 0.1 1 10 1000
Risk Ratio
IV, Random, 95% CI
Favours IBD Favours Gen.
Population
Subgroup
Total (95% CI)
Heterogeneity: Tau2 = 0.9262; Chi2 = 109152.33, df = 24 (P = 0); I2 = 100%
Residual heterogeneity: Tau2 = NA; Chi2 = 109081.17, df = 23 (P = 0); I2 = 100%
group = IBD
group = Gen. Population
Total (95% CI)
Total (95% CI)
Heterogeneity: Tau2 = 4.2172; Chi2 = 802.13, df = 17 (P < 0.01); I2 = 98%
Heterogeneity: Tau2 = 0.9233; Chi2 = 108279.04, df = 6 (P = 0); I2 = 100%
Allocca M et al
An P et al
Foteinogiannopoulou et al
Grassia R et al
Grunert PC et al
Gubatan J et al
Hormati A et al
Khan N et al
Lukin DJ et al
Mak JWY et al (1)
Mak JWY et al (2)
Marafini I et al
Mosli M et al
Norsa L et al
Scaldaferri F et al
Singh S et al
Taxonera C et al
Yu M et al
Gubatan J et al
Mak JWY et al (1)
Mak JWY et al (2)
Marafini I et al
Norsa L et al
Singh S et al
Taxonera C et al
Study or
Events
15
0
0
1
0
5
8
36
29
0
0
3
6
0
5
232
12
0
1155
1017
429
205463
6471
19776
43877
Total
108498842
253625
108245217
6000
318
78
251
415
168
150
37857
119
2954
3091
672
1156
522
1451
196403
1918
102
14067
75210
60956
60317000
1114590
40000000
6663394
Weight
100.0%
62.3%
37.7%
5.0%
1.7%
1.7%
2.6%
1.7%
4.4%
4.7%
5.2%
5.1%
1.7%
1.7%
4.0%
4.6%
1.7%
4.4%
5.4%
4.9%
1.7%
5.4%
5.4%
5.4%
5.4%
5.4%
5.4%
5.4%
IV, Random, 95% CI
5.60 [ 3.62; 8.64]
4.02 [ 1.44; 11.17]
6.59 [ 3.25; 13.35]
2.50 [ 1.40; 4.12]
0.00 [ 0.00; 11.53]
0.00 [ 0.00; 46.19]
3.98 [ 0.10; 22.00]
0.00 [ 0.00; 8.85]
29.76 [ 9.73; 68.08]
53.33 [ 23.30; 102.38]
0.95 [ 0.67; 1.32]
243.70 [169.68; 330.89]
0.00 [ 0.00; 1.25]
0.00 [ 0.00; 1.19]
4.46 [ 0.92; 12.99]
5.19 [ 1.91; 11.26]
0.00 [ 0.00; 7.04]
3.45 [ 1.12; 8.02]
1.18 [ 1.03; 1.34]
6.26 [ 3.24; 10.90]
0.00 [ 0.00; 35.52]
82.11 [ 77.62; 86.77]
13.52 [ 12.71; 14.37]
7.04 [ 6.39; 7.73]
3.41 [ 3.39; 3.42]
5.81 [ 5.67; 5.95]
0.49 [ 0.49; 0.50]
6.58 [ 6.52; 6.65]
Events per 1000 observations
0 50 100 150 200 250 300
Events per 1000 observations
IV, Random, 95% CI
Incidence of COVID-19 in IBD vs General Population
Incidence
Risk ratio
Figure 2. Pooled incidence of COVID in IBD and the general population and relative risk of COVID infection in IBD patients as
compared to the general population. The pooled summary was computed by a random effect approach. CI: confidence interval;
COVID: coronavirus disease; IBD: inflammatory bowel disease.
Singh et al. 9
Figure 2). When the nine studies reporting the risk in
UC and CD were compared for the overall RR, the risk
was not different between the two (RR 1.03, 0.62–1.71;
I
2
¼0) (Supplementary Figure 2).
Some studies provided data regarding the use of var-
ious drugs in patients acquiring COVID-19 and those
who did not acquire COVID-19. On pooled analysis of
this data, the risk ratios of contracting COVID-19 with
various drugs were as follows: for 5-ASA 1.89 (1.23–
2.93; I
2
¼37%); steroids 1.64 (1–2.7; I
2
¼0%); immuno-
modulator 1.55 (0.97–2.48; I
2
¼0%); anti-TNF 1.08
(0.68–1.71; I
2
¼0%); vedolizumab 2.31 (1–5.36;
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.0548; Chi2 = 3.16, df = 2 (P = 0.21); I2 = 37%
Gubatan J et al
Lukin DJ et al
Mosli M et al
Events
4
11
3
Total
40
5
29
6
COVID Pos
Events
54
27
249
Total
1403
163
90
1150
COVID Neg
Weight
100.0%
42.1%
36.0%
22.0%
IV, Random, 95% CI
1.89 [1.23; 2.93]
2.41 [1.48; 3.94]
1.26 [0.72; 2.22]
2.31 [1.03; 5.18]
Risk Ratio
0.2 0.5 1 2 5
Risk Ratio
IV, Random, 95% CI
Favours ASA Favours no ASA
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 1.93, df = 4 (P = 0.75); I2 = 0%
Gubatan J et al
Khan N et al
Lukin DJ et al
Mosli M et al
Taxonera C et al
Events
1
2
2
1
6
Total
88
5
36
29
6
12
COVID Pos
Events
14
2389
3
279
547
Total
41130
163
37821
90
1150
1906
COVID Neg
Weight
100.0%
6.6%
12.1%
7.2%
6.8%
67.3%
IV, Random, 95% CI
1.55 [0.97; 2.48]
2.33 [0.38; 14.42]
0.88 [0.23; 3.38]
2.07 [0.36; 11.78]
0.69 [0.11; 4.12]
1.74 [0.99; 3.08]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours
Immunomodulator
Favours no
Immunomodulator
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.1768; Chi2 = 4.79, df = 4 (P = 0.31); I2 = 17%
Grassia R et al
Gubatan J et al
Lukin DJ et al
Mosli M et al
Taxonera C et al
Events
0
0
7
0
1
Total
53
1
5
29
6
12
COVID Pos
Events
10
10
16
53
17
Total
3559
250
163
90
1150
1906
COVID Neg
Weight
100.0%
11.5%
8.8%
54.7%
9.0%
16.0%
IV, Random, 95% CI
2.31 [1.00; 5.36]
7.95 [0.77; 82.50]
1.42 [0.09; 21.21]
1.36 [0.62; 2.97]
1.65 [0.11; 24.03]
9.34 [1.35; 64.71]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours
Vedolizumab
Favours no
Vedolizumab
Risk of contracting COVID-19 with various drugs
ASA
Immunomodulator
Vedolizumab
Figure 3. Pooled risk ratio of COVID infection in IBD patients depending on use of various drugs (5-ASA, steroids, immuno-
modulators, biological agents, anti-TNF, vedolizumab, ustekinumab). The pooled summary was computed by a random effect
approach. 5-ASA: aminosalicylic acid; CI: confidence interval; COVID: coronavirus disease; IBD: inflammatory bowel disease; TNF:
tumour necrosis factor.
10 United European Gastroenterology Journal 0(0)
I
2
¼17%) and ustekinumab 3.16 (0.55–18.07; I
2
¼72%)
(Figure 3).
Outcomes for IBD patients with COVID-19
The hospitalisation rates in the 11 included studies
varied from 0% to 66.67%. The pooled hospitalisation
rate was 27.99% (21.92–34.99; I
2
¼76%) (Figure 4).
The pooled proportion of patients needing ICU care
was 5.33% (4.46–6.36; I
2
¼0) based on data from nine
studies (Figure 4). The pooled mortality rate in patients
with IBD with COVID-19 was 4.27% (2.39–7.53;
I
2
¼51%) and mortality rates varied from 0% to
33.3% in the 13 studies which were included (Figure 4).
The overall risk of hospitalisation was higher in
patients with UC (RR 1.55, 1.22–1.97; I
2
¼15%)
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 1.07, df = 2 (P = 0.59); I2 = 0%
Gubatan J et al
Lukin DJ et al
Mosli M et al
Events
1
13
1
Total
40
5
29
6
COVID Pos
Events
33
22
237
Total
1403
163
90
1150
COVID Neg
Weight
100.0%
7.9%
84.4%
7.7%
IV, Random, 95% CI
1.64 [1.00; 2.70]
0.99 [0.17; 5.85]
1.83 [1.07; 3.16]
0.81 [0.13; 4.86]
Risk Ratio
0.2 0.5 1 2 5
Risk Ratio
IV, Random, 95% CI
Favours
Steroid
Favours no
Steroid
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 2.91, df = 5 (P = 0.71); I2 = 0%
Grassia R et al
Gubatan J et al
Khan N et al
Lukin DJ et al
Mosli M et al
Taxonera C et al
Events
0
1
3
6
2
3
Total
89
1
5
36
29
6
12
COVID Pos
Events
30
33
4917
18
464
257
Total
41380
250
163
37821
90
1150
1906
COVID Neg
Weight
100.0%
4.1%
6.8%
18.4%
31.8%
16.8%
22.2%
IV, Random, 95% CI
1.08 [0.68; 1.71]
2.74 [0.28; 26.97]
0.99 [0.17; 5.85]
0.64 [0.22; 1.89]
1.03 [0.45; 2.36]
0.83 [0.27; 2.57]
1.85 [0.69; 4.97]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours
Anti−TNF
Favours no
Anti−TNF
Study
Total (95% CI)
Heterogeneity: Tau2 = 2.6741; Chi2 = 14.35, df = 4 (P < 0.01); I2 = 72%
Grassia R et al
Gubatan J et al
Lukin DJ et al
Mosli M et al
Taxonera C et al
Events
0
0
4
0
1
Total
53
1
5
29
6
12
COVID Pos
Events
1
4
25
74
22
Total
3559
250
163
90
1150
1906
COVID Neg
Weight
100.0%
16.9%
16.8%
27.1%
17.4%
21.7%
IV, Random, 95% CI
3.16 [0.55; 18.07]
55.67 [3.49; 887.51]
3.30 [0.20; 54.07]
0.50 [0.19; 1.31]
1.19 [0.08; 17.19]
7.22 [1.06; 49.34]
Risk Ratio
0.01 0.1 1 10 100
Risk Ratio
IV, Random, 95% CI
Favours
Ustekinumab
Favours no
Ustekinumab
Steroid
Anti-TNF
Ustekinumab
Risk of contracting COVID-19 with various drugs
Figure 3. Continued.
Singh et al. 11
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.1559; Chi2 = 40.95, df = 10 (P < 0.01); I2 = 76%
Allocca M et al
Axelrad JE et al
Bezzio C et al
Gonzalez HA et al
Haberman R et al
Marafini I et al
Rodriguez−Lago I et al
Scaldaferri F et al
SECURE IBD
Singh S et al
Taxonera C et al
Events
5
7
22
44
4
2
21
0
512
56
8
Total
2486
15
83
79
150
37
3
40
5
1830
232
12
Weight
100.0%
6.0%
8.8%
12.6%
14.7%
6.3%
1.7%
10.8%
1.2%
17.4%
15.4%
5.2%
IV, Random, 95% CI
27.99 [21.92; 34.99]
33.33 [11.82; 61.62]
8.43 [ 3.46; 16.61]
27.85 [18.35; 39.07]
29.33 [22.19; 37.31]
10.81 [ 3.03; 25.42]
66.67 [ 9.43; 99.16]
52.50 [36.13; 68.49]
0.00 [ 0.00; 52.18]
27.98 [25.93; 30.10]
24.14 [18.78; 30.17]
66.67 [34.89; 90.08]
Events per 100 observations
0 20406080
Events per 100 observations
IV, Random, 95% CI
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 5.88, df = 8 (P = 0.66); I2 = 0%
Allocca M et al
Axelrad JE et al
Gonzalez HA et al
Haberman R et al
Lukin DJ et al
Rodriguez−Lago I et al
Scaldaferri F et al
SECURE IBD
Taxonera C et al
Events
0
1
10
0
3
0
0
99
1
Total
2252
15
83
150
37
80
40
5
1830
12
Weight
100.0%
0.4%
0.9%
8.5%
0.4%
2.6%
0.5%
0.4%
85.4%
0.8%
IV, Random, 95% CI
5.33 [4.46; 6.36]
0.00 [0.00; 21.80]
1.20 [0.03; 6.53]
6.67 [3.24; 11.92]
0.00 [0.00; 9.49]
3.75 [0.78; 10.57]
0.00 [0.00; 8.81]
0.00 [0.00; 52.18]
5.41 [4.42; 6.55]
8.33 [0.21; 38.48]
Events per 100 observations
0 1020304050
Events per 100 observations
IV, Random, 95% CI
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.4443; Chi2 = 24.46, df = 12 (P = 0.02); I2 = 51%
Allocca M et al
Axelrad JE et al
Bezzio C et al
Gonzalez HA et al
Gubatan J et al
Haberman R et al
Hormati A et al
Lukin DJ et al
Marafini I et al
Rodriguez−Lago I et al
Scaldaferri F et al
SECURE IBD
Taxonera C et al
Events
0
1
6
2
1
0
0
0
1
2
0
63
2
Total
2489
15
83
79
150
5
37
150
80
3
40
5
1830
12
Weight
100.0%
3.8%
6.5%
15.1%
9.9%
5.6%
3.8%
3.8%
3.8%
4.9%
9.7%
3.6%
20.5%
9.0%
IV, Random, 95% CI
4.27 [2.39; 7.53]
0.00 [0.00; 21.80]
1.20 [0.03; 6.53]
7.59 [2.84; 15.80]
1.33 [0.16; 4.73]
20.00 [0.51; 71.64]
0.00 [0.00; 9.49]
0.00 [0.00; 2.43]
0.00 [0.00; 4.51]
33.33 [0.84; 90.57]
5.00 [0.61; 16.92]
0.00 [0.00; 52.18]
3.44 [2.66; 4.38]
16.67 [2.09; 48.41]
Events per 100 observations
0 20406080
Events per 100 observations
IV, Random, 95% CI
ICU stay
Mortality
Outcomes in IBD with COVID-19
Hospitalization
Figure 4. The pooled prevalence of various outcomes (hospitalisation, need for ICU and mortality) in IBD patients with COVID.
The pooled summary was computed by a random effect approach. CI: confidence interval; COVID: coronavirus disease; IBD:
inflammatory bowel disease; ICU: intensive care unit.
12 United European Gastroenterology Journal 0(0)
(Figure 5). The risk of need for ICU care was statisti-
cally similar between the two groups (RR 1.42, 0.97–
2.07; I
2
¼0%) (Figure 5). However, the risk of mortality
was higher in patients with UC infected with COVID-
19 as compared to CD (RR 1.94, 1.22–3.10; I
2
¼0%)
(Figure 5).
Impact of IBD drugs on COVID-19 outcomes
The relative risk of hospitalisation (1.59, 1.39–1.82;
I
2
¼0), need for ICU care (2.38, 1.26–4.48; I
2
¼18) and
mortality (2.62, 1.67–4.11; I
2
¼0) were higher with the
use of 5-ASA (Figure 6). The RR of hospitalisation
(1.99, 1.64–2.40; I
2
¼3%), need for ICU (3.41, 2.28–
5.11; I
2
¼0) and mortality (2.70, 1.61–4.55; I
2
¼0) were
higher with the use of steroids (Figure 6). The RR of
hospitalisation (0.89, 0.37–2.10; I
2
¼83%), need for
ICU (0.71, 0.17–3.02; I
2
¼45%) and mortality (1.18,
0.23–6.01; I
2
¼55%) were similar irrespective of the
use of immunomodulators (Figure 6). The RR of hos-
pitalisation (0.34, 0.19–0.61; I
2
¼67%), need for ICU
(0.49, 0.33–0.72; I
2
¼0) and mortality (0.22, 0.13–0.38;
I
2
¼0) were lower with the use of biological agents
(Figure 6).
Assessment of heterogeneity
The heterogeneity assessment was conducted for the
incidence of COVID-19 among the IBD and general
population and outcome assessment (mortality and
hospitalisation) among the patients with IBD with
COVID-19. The leave-one-out analysis for the inci-
dence of COVID-19 among IBD and the general pop-
ulation did not lead to a significant change in
heterogeneity. The detailed information is provided in
Supplementary figures 3 and 4.
Risk of bias
The risk of bias of included studies for the incidence of
COVID-19 infection and the outcomes of COVID-19
infection in IBD patients is summarised in
Supplementary Tables 4 and 5. As the Joanna Briggs
guidance suggests against using a score cut-off for qual-
ity assessment we also did not score the studies.
30
Discussion
IBD is associated with an increased risk of infection
and this risk is related to many factors such as disease
activity, malnutrition and the use of immunosuppres-
sive drugs. It is important for clinicians and patients to
be aware if there is a heightened risk of COVID-19
infection in IBD and if it affects the outcomes. An
increased expression of ACE-2 in the intestinal tract
(even higher than the lung alveoli) has been
demonstrated and proposed as an alternative pathway
of acquiring coronavirus infection.
31
The studies
reporting about changes in ACE-2 expression in the
intestine in patients with IBD have conflicting
results.
3,4
It is pertinent to note that although an
increased expression of ACE-2 in colonic mucosa was
shown in IBD patients on immunohistochemistry, the
functional activity was significantly lower in the
inflamed areas.
32
The ACE-2 which acts as a receptor
for SARS-CoV-2 virus is distinct from the soluble form
of ACE-2, and the soluble form could prevent binding
of the viral particles to the surface ACE-2.
33
The findings of the present meta-analysis suggest
that the risk of COVID-19 in IBD is not different
from the general population. The risk of acquisition
also does not seem to be affected by the type of IBD;
that is, UC or CD. Furthermore, the risk of acquisition
of COVID-19 in IBD is not affected by the drugs used
for treatment of IBD except for 5-ASA. In COVID-19-
positive patients with IBD, hospitalisation was needed
in 27% of patients while the mortality rate was under
5%. The risk of adverse outcomes (hospitalisation and
mortality) were higher in patients with UC. The use of
5-ASA or steroids was also associated with adverse
outcomes (hospitalisation, ICU admission and mortal-
ity) while biological agents were protective.
The increased risk of adverse outcomes in UC as
compared to CD could be due to the fact that patients
with UC are more likely to be of older age. The usage
of various drugs is also likely to be different in UC and
CD, with patients having UC being more likely to
receive 5-ASA whereas those with CD are more likely
to receive biological agents.
34
It is also unclear if bio-
logical differences in the two conditions, including the
differences in expression of ACE-2 and transmembrane
protease serine-2 (TMPRSS-2), could be responsible
for differences in the outcomes.
3,4
The reasons for the
increased risk of COVID-19 infection with 5-ASA are
unclear but this may be related to the fact that 5-ASA
use may be a proxy for underlying UC. It has been
shown that the expression of ACE-2 receptor is
increased to a larger degree in patients with UC.
3
In
addition, a higher proportion of older IBD patients
have UC and hence are more likely to be tested due
to a higher likelihood of symptomatic disease.
Another notable finding is the association of drugs
used in IBD with clinical outcomes following COVID-
19. While the use of 5-ASA and steroids was associated
with an increased risk of hospitalisation, ICU admis-
sion and mortality, the use of biological agents was
associated with a reduction in these outcomes. These
findings support the recommendations of various
expert groups to limit the use of steroids and lower
the dosages in the setting of the pandemic.
Conversely, dexamethasone has been shown in a
Singh et al. 13
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.0187; Chi2 = 7.03, df = 6 (P = 0.32); I2 = 15%
Allocca M et al
Axelrad JE et al
Bezzio C et al
Gonzalez HA et al
Haberman R et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
3
3
17
27
3
258
5
0
Total
981
6
27
46
65
17
812
5
3
UC
Events
2
4
5
17
1
252
3
0
Total
1220
9
56
32
82
20
1010
7
4
CD
Weight
100.0%
2.6%
2.7%
6.6%
17.1%
1.2%
61.1%
8.7%
0.0%
IV, Random, 95% CI
1.55 [1.22; 1.97]
2.25 [0.52; 9.70]
1.56 [0.37; 6.47]
2.37 [0.97; 5.76]
2.00 [1.20; 3.34]
3.53 [0.40; 30.88]
1.27 [1.10; 1.48]
2.14 [1.00; 4.61]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours UC Favours CD
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 0.68, df = 2 (P = 0.71); I2 = 0%
Allocca M et al
Axelrad JE et al
Haberman R et al
Rodriguez−Lago et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
0
0
0
52
1
0
Total
897
6
27
17
27
812
5
3
UC
Events
0
1
0
0
46
0
0
Total
1119
9
56
20
13
1010
7
4
CD
Weight
100.0%
0.0%
1.4%
0.0%
0.0%
97.0%
1.6%
0.0%
IV, Random, 95% CI
1.42 [0.97; 2.07]
0.68 [0.03; 16.27]
1.41 [0.96; 2.07]
4.09 [0.20; 82.62]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours UC Favours CD
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 1.54, df = 4 (P = 0.82); I2 = 0%
Allocca M et al
Axelrad JE et al
Bezzio C et al
Haberman R et al
Rodriguez−Lago et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
0
5
0
2
37
2
0
Total
943
6
27
46
17
27
812
5
3
UC
Events
0
1
1
0
0
25
0
0
Total
1151
9
56
32
20
13
1010
7
4
CD
Weight
100.0%
0.0%
2.2%
5.0%
0.0%
2.5%
87.7%
2.7%
0.0%
IV, Random, 95% CI
1.94 [1.22; 3.10]
0.68 [0.03; 16.27]
3.48 [0.43; 28.38]
2.45 [0.13; 47.64]
1.84 [1.12; 3.03]
6.82 [0.40; 115.54]
Risk Ratio
0.01 0.1 1 10 100
Risk Ratio
IV, Random, 95% CI
Favours UC Favours CD
Hospitalization
ICU stay
Mortality
Outcomes between UC vs CD with COVID-19
Figure 5. The pooled relative risk of various outcomes (hospitalisation, need for ICU and mortality) in UC versus CD. The pooled
summary was computed by a random effect approach. CD: Crohn’s disease; CI: confidence interval; ICU: intensive care unit; UC:
ulcerative colitis.
14 United European Gastroenterology Journal 0(0)
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 0.63, df = 4 (P = 0.96); I2 = 0%
Allocca M et al
Axelrad JE et al
Gonzalez HA et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
2
17
213
4
0
Total
635
1
13
41
572
4
4
ASA +ve
Events
4
5
27
299
4
0
Total
1458
13
70
106
1258
8
3
ASA −ve
Weight
100.0%
0.3%
0.8%
7.7%
86.7%
4.6%
0.0%
IV, Random, 95% CI
1.59 [1.39; 1.82]
1.00 [0.09; 10.87]
2.15 [0.47; 9.94]
1.63 [1.00; 2.65]
1.57 [1.35; 1.81]
1.89 [1.00; 3.56]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours ASA Favours no ASA
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.0037; Chi2 = 3.10, df = 3 (P = 0.38); I2 = 3%
Allocca M et al
Axelrad JE et al
Gonzalez HA et al
SECURE IBD
Turner D et al
Events
2
1
6
98
0
Total
222
2
10
12
197
1
Steroid +ve
Events
2
6
39
414
0
Total
1859
12
73
135
1633
6
Steroid −ve
Weight
100.0%
2.9%
0.9%
8.8%
87.4%
0.0%
IV, Random, 95% CI
1.99 [1.64; 2.40]
5.00 [1.65; 15.15]
1.22 [0.16; 9.09]
1.73 [0.93; 3.23]
1.96 [1.67; 2.31]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours Steroid Favours no Steroid
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.6909; Chi2 = 24.10, df = 4 (P < 0.01); I2 = 83%
Allocca M et al
Axelrad JE et al
Gonzalez HA et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
2
1
8
115
3
0
Total
450
3
6
71
360
6
4
ImmMod +ve
Events
2
6
36
397
5
0
Total
1643
11
77
76
1470
6
3
ImmMod −ve
Weight
100.0%
15.3%
11.5%
23.7%
27.7%
21.7%
0.0%
IV, Random, 95% CI
0.89 [0.37; 2.10]
3.67 [0.83; 16.22]
2.14 [0.31; 14.99]
0.24 [0.12; 0.48]
1.18 [1.00; 1.41]
0.60 [0.25; 1.44]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours
Immunomodulator
Favours no
Immunomodulator
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.2517; Chi2 = 12.31, df = 4 (P = 0.02); I2 = 67%
Allocca M et al
Axelrad JE et al
Gonzalez HA et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
2
3
11
209
2
0
Total
1227
11
58
96
1053
5
4
Biologic +ve
Events
2
4
33
303
6
0
Total
866
3
25
51
777
7
3
Biologic −ve
Weight
100.0%
11.0%
11.7%
26.4%
35.2%
15.8%
0.0%
IV, Random, 95% CI
0.34 [0.19; 0.61]
0.27 [0.06; 1.21]
0.32 [0.08; 1.34]
0.18 [0.10; 0.32]
0.51 [0.44; 0.59]
0.47 [0.15; 1.42]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours Biolo
g
ics Favours no Biolo
g
ics
Steroid
Immunomodulator
Biologicals
Outcome of various drugs in IBD with COVID-19
Hospitalization
ASA
Figure 6. The pooled relative risk of various outcomes (hospitalisation, need for ICU and mortality) in IBD COVID patients with
respect to the use of various drugs (5-ASA, steroids, immunomodulators, biological agents, anti-TNF, vedolizumab, ustekinu-
mab). The pooled summary was computed by a random effect approach. 5-ASA: aminosalicylic acid; CI: confidence interval; IBD:
inflammatory bowel disease; ICU: intensive care unit; TNF: tumour necrosis factor.
Singh et al. 15
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.1091; Chi2 = 3.68, df = 3 (P = 0.30); I2 = 18%
Allocca M et al
Axelrad JE et al
Gonzalez HA et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
1
6
44
1
0
Total
635
1
13
41
572
4
4
ASA +ve
Events
0
0
4
55
0
0
Total
1458
13
70
106
1258
8
3
ASA −ve
Weight
100.0%
0.0%
3.9%
21.2%
70.7%
4.3%
0.0%
IV, Random, 95% CI
2.38 [1.26; 4.48]
15.67 [0.67; 364.58]
3.88 [1.15; 13.04]
1.76 [1.20; 2.58]
5.67 [0.29; 112.65]
Risk Ratio
0.01 0.1 1 10 100
Risk Ratio
IV, Random, 95% CI
Favours ASA Favours no ASA
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 0.06, df = 1 (P = 0.81); I2 = 0%
Allocca M et al
Axelrad JE et al
SECURE IBD
Turner D et al
Events
0
0
29
0
Total
210
2
10
197
1
Steroid +ve
Events
0
1
70
0
Total
1724
12
73
1633
6
Steroid −ve
Weight
100.0%
0.0%
1.7%
98.3%
0.0%
IV, Random, 95% CI
3.41 [2.28; 5.11]
2.33 [0.10; 53.62]
3.43 [2.29; 5.16]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours Steroid Favours no Steroid
Study
Total (95% CI)
Heterogeneity: Tau2 = 0.9913; Chi2 = 5.43, df = 3 (P = 0.14); I2 = 45%
Allocca M et al
Axelrad JE et al
Gonzalez HA et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
0
0
14
1
0
Total
450
3
6
71
360
6
4
ImmMod +ve
Events
0
1
10
85
0
0
Total
1643
11
77
76
1470
6
3
ImmMod −ve
Weight
100.0%
0.0%
15.5%
17.7%
50.6%
16.2%
0.0%
IV, Random, 95% CI
0.71 [0.17; 3.02]
3.97 [0.18; 88.13]
0.05 [0.00; 0.85]
0.67 [0.39; 1.17]
3.00 [0.15; 60.88]
Risk Ratio
0.01 0.1 1 10 100
Risk Ratio
IV, Random, 95% CI
Favours
Immunomodulator
Favours no
Immunomodulator
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 0.58, df = 2 (P = 0.75); I2 = 0%
Allocca M et al
Axelrad JE et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
0
40
0
0
Total
1131
11
58
1053
5
4
Biologic +ve
Events
0
1
59
1
0
Total
815
3
25
777
7
3
Biologic −ve
Weight
100.0%
0.0%
1.5%
96.9%
1.6%
0.0%
IV, Random, 95% CI
0.49 [0.33; 0.72]
0.15 [0.01; 3.45]
0.50 [0.34; 0.74]
0.45 [0.02; 9.18]
Risk Ratio
0.01 0.1 1 10 100
Risk Ratio
IV, Random, 95% CI
Favours Biolo
g
ics Favours no Biolo
g
ics
Steroid
Immunomodulator
Biologicals
Outcome of various drugs in IBD with COVID-19
ICU
ASA
Figure 6. Continued.
16 United European Gastroenterology Journal 0(0)
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 0.90, df = 3 (P = 0.83); I2 = 0%
Allocca M et al
Axelrad JE et al
Bezzio C et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
0
3
34
2
0
Total
618
1
13
24
572
4
4
ASA +ve
Events
0
1
3
29
0
0
Total
1407
13
70
55
1258
8
3
ASA −ve
Weight
100.0%
0.0%
2.1%
8.8%
86.6%
2.6%
0.0%
IV, Random, 95% CI
2.62 [1.67; 4.11]
1.74 [0.07; 40.51]
2.29 [0.50; 10.55]
2.58 [1.59; 4.19]
9.44 [0.57; 157.37]
Risk Ratio
0.01 0.1 1 10 100
Risk Ratio
IV, Random, 95% CI
Favours ASA Favours no ASA
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 0.24, df = 2 (P = 0.89); I2 = 0%
Allocca M et al
Axelrad JE et al
Bezzio C et al
SECURE IBD
Turner D et al
Events
0
0
2
15
0
Total
219
2
10
9
197
1
Steroid +ve
Events
0
1
4
48
0
Total
1794
12
73
70
1633
6
Steroid −ve
Weight
100.0%
0.0%
2.8%
11.3%
86.0%
0.0%
IV, Random, 95% CI
2.70 [1.61; 4.55]
2.33 [0.10; 53.62]
3.89 [0.83; 18.30]
2.59 [1.48; 4.54]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours Steroid Favours no Steroid
Study
Total (95% CI)
Heterogeneity: Tau2 = 1.4662; Chi2 = 6.68, df = 3 (P = 0.08); I2 = 55%
Allocca M et al
Axelrad JE et al
Bezzio C et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
1
0
10
0
0
Total
385
3
6
6
360
6
4
ImmMod +ve
Events
0
0
6
53
2
0
Total
1640
11
77
73
1470
6
3
ImmMod −ve
Weight
100.0%
0.0%
17.3%
19.9%
43.5%
19.3%
0.0%
IV, Random, 95% CI
1.18 [0.23; 6.01]
35.77 [1.61; 793.15]
0.87 [0.05; 13.78]
0.77 [0.40; 1.50]
0.20 [0.01; 3.41]
Risk Ratio
0.01 0.1 1 10 100
Risk Ratio
IV, Random, 95% CI
Favours
Immunomodulator
Favours no
Immunomodulator
Study
Total (95% CI)
Heterogeneity: Tau2 = 0; Chi2 = 1.46, df = 3 (P = 0.69); I2 = 0%
Allocca M et al
Axelrad JE et al
Bezzio C et al
SECURE IBD
Taxonera C et al
Turner D et al
Events
0
1
1
14
0
0
Total
1178
11
58
47
1053
5
4
Biologic +ve
Events
0
0
5
49
2
0
Total
847
3
25
32
777
7
3
Biologic −ve
Weight
100.0%
0.0%
3.0%
6.8%
86.6%
3.7%
0.0%
IV, Random, 95% CI
0.22 [0.13; 0.38]
1.31 [0.06; 31.03]
0.14 [0.02; 1.11]
0.21 [0.12; 0.38]
0.27 [0.02; 4.62]
Risk Ratio
0.1 0.5 1 2 10
Risk Ratio
IV, Random, 95% CI
Favours Biolo
g
ics Favours no Biolo
g
ics
ASA
Steroid
Immunomodulator
Biologicals
Outcome of various drugs in IBD with COVID-19
Mortality
Figure 6. Continued.
Singh et al. 17
well-powered randomised study (RECOVERY trial) to
improve the outcomes in patients with severe COVID
disease. Therefore, the findings of our meta-analysis
could represent the fact that steroid use is a proxy for
the subset of patients with active IBD who are predis-
posed to adverse outcomes. Another finding is that
5-ASA use is associated with adverse outcomes,
which is difficult to explain by the biological action
of 5-ASA. 5-ASA acts through peroxisome
proliferator-activated receptor (PPAR)-gamma which
should attenuate the inflammatory response.
However, 5-ASA use could be an indicator of underly-
ing UC and active disease and thereby associated with
adverse outcomes. Finally, the use of biological agents
was associated with a reduction in adverse outcomes.
Because of the limited number of studies, we did not
stratify this comparison for various groups of biologi-
cal agents. However, it has been suggested that anti-
TNF could be beneficial in COVID-19 disease by atten-
uating the hyperinflammatory response known as cyto-
kine storm.
35
The drug, anecdotally, has been shown to
be efficacious in improving COVID-19 disease and is
subject to a controlled trial.
This systematic review provides some guidance for
the care of these patients and suggests that steroid use
may be avoided in the setting of the pandemic while the
use of biological agents can be continued.
Furthermore, with the potential of new surges in vari-
ous locations, the results of our meta-analysis could
guide clinicians and patients regarding the continuation
of IBD medication in such scenarios. However, the
results of this study should be looked at taking into
consideration the limitations. Incidence in the included
studies is reported from different geographical loca-
tions with different genetic composition of the popula-
tion, medication used for IBD, comorbidities and
hygiene practices, which may affect the underlying
risk of acquisition of SARS-CoV-2 infection. Also,
some studies evaluated only the symptomatic individu-
als for COVID-19. Because of the limited availability
of data, the confounding effect of older age, comorbid-
ities, active disease and the combination of IBD med-
ications on the risk of COVID-19 acquisition and
outcome could not be evaluated. In particular, one
study which evaluated the age standardised incidence
of COVID in IBD patients suggested that the risk in
the IBD population may be overestimated.
8
Unfortunately, as similar data were not available
from other studies, an analysis to account for differ-
ences of risk with age could not be performed.
However, analysis from studies with a mean age of
less than 45 years or over 45 years suggests that the
incidence of COVID was higher in studies with a great-
er mean age. Furthermore, as SECURE-IBD are
registry-based data, there may be a risk of the
duplication of data. Also, the number of studies was
limited especially for some analyses like the effect of
various drug treatments on the outcomes.
A number of unanswered questions remain and
require further research. Prospective studies should
evaluate the risk of COVID-19 and its outcome based
on the underlying disease activity of IBD stratified by
treatments. To know the true risk of asymptomatic
infection, further research should use serological test-
ing to identify the actual infection rate in IBD as well as
the general population. Basic research should also
focus on differences in intestinal mucosal ACE-2
expression in relation to various drugs and their
impact on clinical outcomes.
To conclude, the present meta-analysis suggests that
the risk of COVID in IBD patients is not higher than
the general population. Also, the outcomes of COVID
in IBD may be adversely affected by the type of disease
(UC) and the use of 5-ASA or steroids. The use of
biological agents, in contrast, seems to be associated
with better outcomes.
Author contributions
Conception: VS, SS; literature search: AKS, VS; screening:
AKS, AJ, VS; data extraction: AKS, AJ; RoB: AKS, AJ;
data analysis: PKM; initial draft: AKS, PKM, AJ, VS; man-
uscript revision for important intellectual content: VS and SS;
final approval: all authors.
Declaration of conflicting interests
The author(s) have no conflicts of interest to declare.
Funding
The author(s) received no financial support for the resarch,
authorship, and/or publication of this article.
Ethics approval
Not applicable as the paper is a systematic review and did not
involve any primary research.
Informed consent
Not applicable as the paper does not involve primary
research on human subjects.
ORCID iDs
Vishal Sharma https://orcid.org/0000-0003-2472-3409
Shaji Sebastian https://orcid.org/0000-0002-3670-6545
Supplemental material
Supplemental material for this article is available online.
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