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Inflammatory Bowel Disease (IBD) pharmacotherapy and the risk of serious infection: a systematic review and network meta-analysis

  • Chelle L. Wheat1, 2Email author,
  • Cynthia W. Ko2,
  • Kindra Clark-Snustad2,
  • David Grembowski1,
  • Timothy A. Thornton4 and
  • Beth Devine1, 3
BMC GastroenterologyBMC series – open, inclusive and trusted201717:52

DOI: 10.1186/s12876-017-0602-0

Received: 8 October 2016

Accepted: 17 March 2017

Published: 14 April 2017

Abstract

Background

The magnitude of risk of serious infections due to available medical therapies of inflammatory bowel disease (IBD) remains controversial. We conducted a systematic review and network meta-analysis of the existing IBD literature to estimate the risk of serious infection in adult IBD patients associated with available medical therapies.

Methods

Studies were identified by a literature search of PubMed, Cochrane Library, Medline, Web of Science, Scopus, EMBASE, and ProQuest Dissertations and Theses. Randomized controlled trials comparing IBD medical therapies with no restrictions on language, country of origin, or publication date were included. A network meta-analysis was used to pool direct between treatment comparisons with indirect trial evidence while preserving randomization.

Results

Thirty-nine articles fulfilled the inclusion criteria; one study was excluded from the analysis due to disconnectedness. We found no evidence of increased odds of serious infection in comparisons of the different treatment strategies against each other, including combination therapy with a biologic and immunomodulator compared to biologic monotherapy. Similar results were seen in the comparisons between the newer biologics (e.g. vedolizumab) and the anti-tumor necrosis factor agents.

Conclusions

No treatment strategy was found to confer a higher risk of serious infection than another, although wide confidence intervals indicate that a clinically significant difference cannot be excluded. These findings provide a better understanding of the risk of serious infection from IBD pharmacotherapy in the adult population.

Prospero registration

The protocol for this systematic review was registered on PROSPERO (CRD42014013497).

Keywords

Inflammatory bowel disease IBD pharmacotherapy Infection Network meta-analysis

Background

Inflammatory bowel disease (IBD) typically requires lifelong medical care for adequate disease management. Medical therapies for IBD include anti-inflammatories such as mesalamine or sulfasalazine, antibiotics, corticosteroids, immunomodulators, and biologic medications, all of which may be used alone or in combination. Each treatment strategy carries the risk of adverse effects and may not adequately manage the patient’s disease.

Corticosteroids, immunomodulators, and biologic medications in particular can have significant adverse effects, possibly including a higher risk of infection. Reactivation of latent infections, such as tuberculosis, is of specific concern with biologic medications [1]. Previous estimates of the proportion of IBD patients with any infection (not limited to serious) following treatment with these medications range from 0.5-30.0%; however there is inconsistency in the reporting of infectious outcomes in the published literature, making the true incidence of infection difficult to determine [2]. In addition, there is conflicting evidence as to whether combinations of therapies modify the risk for serious infection [36]. Furthermore, serious infections in particular are relatively rare, and large cohorts of treated patients are required to determine the incidence for specific medications [2]. Lastly, many of these therapies have never been compared directly to each other in the existing literature.

Understanding the risk for infections associated with IBD pharmacotherapy is a crucial consideration for providers and patients. The aim of this study is to estimate the risk of serious infection from currently available medical therapies in adult IBD patients through a systematic review and network meta-analysis of randomized controlled trials (RCTs). Unique to this study, we compare the risks of serious infection for the different IBD therapies and combinations of therapies, even in situations where medications have not been directly compared in previous studies.

Methods

Literature search

A detailed literature search was conducted to identify all published and unpublished RCTs of IBD pharmacotherapies in adult patients. Due to the heterogeneity in treatment and outcome reporting, observational studies (i.e. cohort, case-control) were excluded from this analysis. The classes of medications included in the search were corticosteroids (e.g. budesonide, prednisone); immunomodulators (e.g. azathioprine, 6-mercaptopurine, methotrexate); anti-inflammatories (e.g. mesalamine, sulfasalazine); antibiotics (e.g. rifaximin); and biologics (e.g. infliximab, adalimumab, certolizumab pegol, golimumab, ustekinumab, vedolizumab). We searched the PubMed, Cochrane Library, Medline, Web of Science, Scopus, EMBASE, and ProQuest Dissertations and Theses databases. Reference lists of published articles were hand searched for secondary sources, and experts in the field contacted for unpublished data. Furthermore, ClinicalTrials.gov, the WHO International Clinical Trial Registry, and scientific information packets of approved IBD pharmacotherapies were scrutinized for additional information sources. No restrictions on language, country of origin, or publication date were used. The duration of investigational treatment and follow-up were required to be at least six weeks each. The date of the final literature search was 17 March 2015. Figure 1 outlines the literature search (Additional file 1: Table S1). The protocol for this systematic review was registered on PROSPERO (CRD42014013497) and can be accessed at: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42014013497
Fig. 1

PRISMA Flowchart depicting the identification of studies, inclusion, and exclusion assessment

Inclusion and exclusion criteria

All RCTs that reported odds ratios (ORs) or provided information sufficient to accurately calculate ORs for serious infection in adult IBD patients were included. Serious infections were defined per the US Food and Drug Administration’s guidelines [7] as one that results in death, is life-threatening, results in hospitalization or prolongs hospitalization, causes disability or permanent damage, or is considered by the reporting investigator as an event that requires medical or surgical intervention to avoid one of these specified outcomes. Studies focusing on pediatric populations, those with incomplete reporting of serious adverse events, those without a comparison group (open-label trials), those of treatment duration and length of follow up less than 6 weeks each, and those not written in English and unable to be translated to English were excluded. If publications reported duplicate data on a population, only the publication with the longest follow-up period was included.

Data collection and quality assessment

Two independent reviewers (CW and KCS) examined each article for inclusion according to the eligibility criteria. Any disagreement was resolved through discussion and consensus. Thirty-nine articles fulfilled the inclusion criteria (Fig. 1) [5, 845].

We retrieved demographic (where possible) and outcome data for each included article using standardized forms. Individual studies were assigned a bias risk rating using the Cochrane Collaboration’s Risk of Bias Assessment Tool [46]. The strength of evidence was assessed utilizing The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach specifically designed for network meta-analysis [47].

Statistical analysis

A network meta-analysis (NMA) technique, also known as mixed treatment comparison methods, was used to compare the risk of serious infection associated with different medications used to treat IBD. This methodological framework allowed us to construct a network of interconnected RCTs from which we could make indirect comparisons between treatments in two trials that have one treatment in common, even in situations where treatments have not been directly compared [4850]. For example, in trial 1 treatment A is compared to treatment B, and in trial 2 treatment B is compared to treatment C. A NMA allows us to make a valid evaluation of treatment A and treatment C although these two therapies were not directly compared in a single study. Through the use of a NMA, we were able to preserve the within trial randomized treatment comparisons, as well as add information from all of the available indirect comparisons between therapies [4850].

The logarithm of the odds ratio (OR) for each trial and its standard error (SE) were calculated in accordance with the intention to treat principle (ITT) and used in the NMA. Each arm of the individual trials was classified according to its primary treatment strategy, and no adjustments were made for variable medication dosage. A fixed value of 0.5 was added where no events were observed in one or both groups of an individual study in order to avoid computational errors. A multivariate random-effects logistic regression model using restricted maximum likelihood (REML) was used to combine estimates. Statistical analysis was performed using Stata SE version 14 (StataCorp, College Station, TX). We performed the NMA using the network suite of commands published by White [51]. Graphs were generated using the published Stata routines of Chaimani [52].

A crucial consideration in any NMA is the evaluation of inconsistency, or incoherence. Indirect evidence can be combined in large samples if the assumption is made that across treatment comparisons, there are no important differences in the types of studies contributing to the comparisons, or in other words that there is consistency [53]. We assessed inconsistency using a design-by-treatment interaction model, which allows for the global testing for the presence of inconsistency in NMAs with multi-arm studies [53]. In addition to inconsistency, the transitivity assumption is important to assess in a NMA. The transitivity assumption asserts that it is equally likely that any patient in the network could have been given any of the other treatments in the network [47]. As all treatment options were randomized the transitivity assumption is satisfied. Visual assessment of a comparison-adjusted funnel plot was used to assess for the presence of publication bias and other small study effects [52]. P-values of ≤ .05 were considered statistically significant.

Results

Table 1 displays a summary of the trials included in the NMA. One of the identified trials did not fit into the connected network because of its treatment comparators (infliximab + MTX + prednisone and infliximab + prednisone), which were not examined in any of the other included trials; thus this trial was excluded and thirty-eight trials were included in the final analysis. Figure 2 illustrates the network of RCTs by treatment strategy. Each node in the network represents a treatment strategy and the connections signify pairwise treatment comparisons from the trials included. The size of the node corresponds to the number of randomly assigned participants (sample size), with a larger node signifying a larger sample size. The width of connecting lines is proportional to the number of trials comparing each pair of therapies. If there is no line connecting two nodes, no studies directly compared the two treatments [54].
Table 1

Characteristics of included studies

Author

Journal

Publication Year

Region of Origin

Number of Sites

Study Durationa (wks)

Diagnosis

Treatment Groups

Number of Patients

Mean Age (yrs)

Female (%)

Ardizzone [8]

Dig Liver Dis

2003

Europe (Western)

1

24

CD

MTX (25 mg/week) + prednisone (40 mg/day)

27

37.0

51.9

AZA (2 mg/kg/day) + prednisone (40 mg/day)

27

31.0

44.0

Ardizzone [9]

Gut

2006

Europe (Western)

1

24

UC

AZA (2 mg/kg/day) + prednisone (40 mg/day)

36

43.0

44.0

5-ASA (3.2 g/day) + prednisone (40 mg/day)

36

45.0

47.0

Arora [10]

Hepatogastroenterol

1999

N America

1

52

CD

MTX (15 mg/week) + prednisone (variable)

15

37.3

20.0

Placebo + prednisone (variable)

18

35.6

55.6

Bar-Meir [11]

Gastroenterology

1998

Middle East

14

8

CD

Budesonide (9 mg/day)

100

32.7

47.0

Prednisone (40 mg/day)

101

32.8

49.5

Bar-Meir [12]

Dis Colon Rectum

2003

Worldwide

38

8

UC

Budesonide foam (2 mg/day)

120

42.0

62.0

Hydrocortisone foam (100 mg/day)

128

42.0

52.0

Colombel [13]

Gastroenterology

2007

Worldwide

92

56

CD

Adalimumab (40 mg/week or 40 mg/eow)

517

NR

61.9

Placebo

261

NR

62.1

Colombel [5]

N Engl J Med

2010

Worldwide

92

50

CD

Infliximab (5 mg/kg)

169

35.0

50.3

AZA (2.5 mg/kg/day)

170

35.0

47.1

Infliximab + AZA

169

34.0

47.9

Cortot [14]

Gut

2001

Worldwide

24

22

CD

Budesonide (6 mg/day) + prednisone (variable)

59

35.0

52.5

Placebo + prednisone (variable)

58

32.0

65.6

D’Haens [15]

Lancet

2008

Europe (Western)

18

104

CD

Infliximab (5 mg/kg) + AZA (2–2.5 mg/kg/day) (or MTX)

67

30.0

66.2

Prednisone (32 mg/day) or budesonide (9 mg/day)

66

28.7

57.8

Ewe [16]

Gastroenterology

1993

Europe (Western)

1

16

CD

AZA (2.5 mg/kg/day) + prednisone (60 mg/day)

21

27.3

NR

Placebo + prednisone (60 mg/day)

21

29.3

NR

Feagan [17]

N Engl J Med

1995

N America

8

16

CD

MTX (25 mg/week) + prednisone (20 mg/day)

94

34.0

46.0

Placebo + prednisone (20 mg/day)

47

36.0

45.0

Feagan [18]

N Engl J Med

2000

N America

7

40

CD

MTX (15 mg/week)

40

32.0

60.0

Placebo

36

34.0

39.0

Feagan [19]

Gastroenterology

2014

Canada

15

50

CD

Infliximab (5 mg/kg) + MTX (25 mg/week) + prednisone (variable)

63

40.4

46.6

       

Infliximab + placebo + prednisone (variable)

63

38.5

41.3

Hanauer [20]

Gastroenterology

2004

N America

5

104

CD

6MP (50 mg/day)

47

34.9

51.0

5-ASA (3 g/day)

44

34.1

57.0

Placebo

40

34.2

55.0

Hawthorne [21]

BMJ

1992

Europe (Western)

5

52

UC

AZA (variable)

40

50.0

62.5

Placebo

39

40.5

33.3

Lemann [22]

Gastroenterology

2006

Europe (Western)

22

52

CD

Infliximab (5 mg/kg) + AZA/6MP (2-3 mg/kg/day or 1–1.5 mg/kg/day) + prednisone (variable)

57

26.5

52.6

AZA/6MP + prednisone

56

27.5

57.1

Mantzaris [23]

Am J Gastroenterol

2004

Europe (Western)

1

104

UC

AZA (2.2 mg/kg/day) + 5-ASA (0.5 g TID)

36

33.0

50.0

AZA

34

35.0

52.9

Neurath [24]

Gut

1999

Europe (Western)

1

24

CD

AZA (2.5 mg/kg/day) + prednisone (50 mg/day)

35

NR

NR

MMF (15 mg/kg/day) + prednisone (50 mg/day)

35

NR

NR

Ochsenkun [25]

Gastroenterology

2003

Not reported

Not reported

13

UC

Infliximab (5 mg/kg)

6

NR

NR

Prednisone (1.5 mg/kg/day)

7

NR

NR

Odonnell [26]

Gut

1992

Europe (Western)

1

6

UC

5-ASA enemas (2 g/day)

24

49.0

28.3

Prednisone enemas (20 mg/day)

21

43.0

61.9

Oren [27]

Gastroenterology

1996

Middle East

12

36

UC

MTX (12.5 mg/day)

30

38.3

43.3

Placebo

37

38.9

51.4

Orth [28]

Am J Gastroenterol

2000

Europe (Western)

1

52

UC

MMF (20 mg/kg/day) + prednisone (50 mg/day)

12

42.4

50.0

AZA (2 mg/kg/day) + prednisone (50 mg/day)

12

40.4

25.0

Prantera [29]

Gastroenterology

2012

Worldwide

55

12

CD

Rifaximin (400 mg/800 mg/1200 mg BID)

308

33.3

56.8

Placebo

102

37.0

59.0

Present [30]

N Engl J Med

1999

Worldwide

12

34

CD

Infliximab (5 mg/kg or 10 mg/kg)

63

38.1

57.1

Placebo

31

35.4

46.0

Rutgeerts [31]

Gastroenterology

1995

Europe (Western)

1

12

CD

Metronidazole (20 mg/kg/day)

30

33.0

NR

Placebo

30

37.0

NR

Rutgeerts [32]

N Engl J Med

2005

Worldwide

62

46

UC

Infliximab (5 mg/kg or 10 mg/kg)

243

42.1

38.3

Placebo

121

41.4

40.5

55

22

UC

Infliximab (5 mg/kg or 10 mg/kg)

241

40.4

40.2

Placebo

123

39.3

42.3

Rutgeerts [33]

Gastroenterology

2005

Europe (Western)

2

54

CD

Ornidazole (1 g/day)

38

35.0

57.9

Placebo

40

30.5

50.0

Sandborn [34]

Gastroenterology

2003

N America

18

10

CD

Tacrolimus (0.2 mg/kg/day)

21

40.8

52.4

Placebo

25

38.1

66.0

Sandborn [35]

N Engl J Med

2005

Worldwide

142

12

CD

Natalizumab (300 mg)

724

38.0

57.0

Placebo

181

39.0

60.0

48

CD

Natalizumab (300 mg)

168

37.0

54.0

Placebo

171

37.0

65.0

Sandborn [36]

Gut

2007

Worldwide

53

56

CD

Adalimumab (variable)

37

36.0

56.8

Placebo

18

36.0

67.0

Sandborn [37]

N Engl J Med

2007

Worldwide

171

26

CD

Certolizumab pegol (400 mg)

331

37.0

53.0

Placebo

329

38.0

60.0

Sandborn [38]

Gastroenterology

2012

Worldwide

103

52

UC

Adalimumab (variable)

248

39.6

42.7

Placebo

246

41.3

38.2

Sandborn [39]

N Engl J Med

2012

Worldwide

153

36

CD

Ustekinumab (variable)

394

38.8

61.2

Placebo

132

39.5

51.5

Sandborn [40]

N Engl J Med

2013

Worldwide

285

52

CD

Vedolizumab (300 mg)

967

35.7

53.4

Placebo

148

38.6

53.4

Sandborn [41]

Gastroenterology

2014

Worldwide

251

52

UC

Golimumab (50 or 100 mg)

308

40.3

46.1

Placebo

156

40.2

51.9

Sands [42]

Inflamm Bowel Dis

2007

N America

17

32

CD

Natalizumab (300 mg) + infliximab (5 mg/kg)

52

39.9

54.0

Placebo + infliximab

27

38.9

37.0

Schreiber [43]

Gastroenterology

2005

Worldwide

58

20

CD

Certolizumab pegol (variable)

219

36.5

48.6

Placebo

73

35.8

67.1

Schreiber [44]

N Engl J Med

2007

Worldwide

147

20

CD

Certolizumab pegol (400 mg)

215

38.0

57.0

Placebo

210

38.0

48.0

Targan [45]

Gastroenterology

2007

Worldwide

114

8

CD

Natalizumab (300 mg)

259

38.1

59.0

Placebo

250

37.7

59.0

Author

Journal

Mean Disease Duration (months)

Surgery (%)

Smoking History (%)

Concomitant Immunomodulatorb Use (%)

Concomitant 5-aminosalicylate Use (%)

Concomitant Steroid Use (%)

Observed Number of Serious Infections

Percentage of Serious Infections (%)

Bias Rating

Ardizzone [8]

Dig Liver Dis

76.6

33.0

NR

0.0

0.0

0.0

0

0.0

Low

57.3

30.0

NR

0.0

0.0

0.0

0

0.0

Ardizzone [9]

Gut

64.4

NR

25.0

0.0

0.0

0.0

0

0.0

Low

67.5

NR

17.0

0.0

0.0

0.0

1

2.8

Arora [1]

Hepatogastroenterol

109.2

26.7

NR

0.0

NR

0.0

1

6.7

Low

140.4

55.6

NR

0.0

NR

0.0

0

0.0

Bar-Meir [11]

Gastroenterology

60.0

15.0

30.0

0.0

0.0

0.0

0

0.0

Low

60.0

23.8

31.0

0.0

0.0

0.0

0

0.0

Bar-Meir [12]

Dis Colon Rectum

42.0

NR

41.0

0.0

52.0

0.0

0

0.0

Low

45.6

NR

30.0

0.0

63.0

0.0

0

0.0

Colombel [13]

Gastroenterology

NR

NR

35.6

51.0

39.3

38.9

14

2.7

Low

NR

NR

35.6

50.6

39.5

38.7

9

3.4

Colombel [5]

N Engl J Med

26.4

NR

NR

0.0

51.5

47.4

8

4.7

Low

28.8

NR

NR

0.0

61.2

38.2

9

5.3

26.4

NR

NR

0.0

50.3

39.0

7

4.1

Cortot [14]

Gut

106.8

30.5

NR

15.3

49.2

0.0

0

0.0

Low

97.2

36.2

NR

8.6

48.3

0.0

0

0.0

D’Haens [15]

Lancet

2.0

NR

55.4

0.0

4.6

0.0

4

6.0

Low

2.5

NR

60.9

0.0

3.1

0.0

7

10.6

Ewe [16]

Gastroenterology

55.2

NR

NR

0.0

57.0

0.0

0

0.0

Low

46.8

NR

NR

0.0

37.0

0.0

0

0.0

Feagan [17]

N Engl J Med

93.0

47.0

49.0

0.0

0.0

0.0

0

0.0

Low

98.0

47.0

47.0

0.0

0.0

0.0

0

0.0

Feagan [18]

N Engl J Med

88.0

43.0

50.0

0.0

0.0

0.0

0

0.0

Low

84.0

36.0

42.0

0.0

0.0

0.0

1

2.8

Feagan [19]

Gastroenterology

130.9

57.1

63.5

0.0

0.0

0.0

0

0.0

Low

115.4

46.0

57.2

0.0

0.0

0.0

0

0.0

Hanauer [20]

Gastroenterology

113.0

100.0

NR

0.0

0.0

0.0

0

0.0

Low

120.0

100.0

NR

0.0

0.0

0.0

0

0.0

127.0

100.0

NR

0.0

0.0

0.0

0

0.0

Hawthorne [21]

BMJ

NR

NR

NR

0.0

80.0

NR

0

0.0

Low

NR

NR

NR

0.0

85.0

NR

0

0.0

Lemann [22]

Gastroenterology

48.0

NR

NR

0.0

0.0

0.0

0

0.0

Low

66.0

NR

NR

0.0

0.0

0.0

3

5.4

Mantzaris [23]

Am J Gastroenterol

60.0

NR

8.0

0.0

0.0

0.0

0

0.0

Low

48.0

NR

6.0

0.0

0.0

0.0

0

0.0

Neurath [24]

Gut

NR

NR

NR

0.0

NR

0.0

0

0.0

Low

NR

NR

NR

0.0

NR

0.0

0

0.0

Ochsenkun [25]

Gastroenterology

NR

NR

NR

NR

NR

NR

0

0.0

Uncertain

NR

NR

NR

NR

NR

NR

0

0.0

Odonnell [26]

Gut

NR

NR

NR

NR

75.0

NR

0

0.0

Low

NR

NR

NR

NR

71.4

NR

0

0.0

Oren [27]

Gastroenterology

95.2

NR

51.7

0.0

66.7

70.0

0

0.0

Low

70.2

NR

51.4

0.0

67.6

73.0

0

0.0

Orth [28]

Am J Gastroenterol

149.0

0.0

NR

0.0

66.7

0.0

2

16.7

Low

87.0

0.0

NR

0.0

66.7

0.0

1

8.3

Prantera [29]

Gastroenterology

40.0

28.6

21.8

25.2

67.4

48.8

1

0.3

Low

39.0

32.0

26.0

27.0

71.0

48.0

0

0.0

Present [30]

N Engl J Med

151.2

60.3

NR

46.0

52.4

34.9

3

4.8

Low

144.0

59.0

NR

29.0

61.0

35.0

0

0.0

Rutgeerts [31]

Gastroenterology

108.0

NR

NR

0.0

0.0

NR

0

0.0

Low

120.0

NR

NR

0.0

0.0

NR

0

0.0

Rutgeerts [32]

N Engl J Med

85.8

NR

46.1

51.4

69.1

58.8

11

4.5

Low

74.4

NR

50.4

43.8

70.2

65.3

5

4.1

79.2

NR

46.9

42.3

75.9

52.3

5

2.1

78.0

NR

48.8

43.9

72.4

48.8

1

0.8

Rutgeerts [33]

Gastroenterology

84.0

100.0

44.7

0.0

0.0

52.3

0

0.0

Low

36.0

100.0

47.5

0.0

0.0

35.0

0

0.0

Sandborn [34]

Gastroenterology

NR

62.0

33.0

62.0

43.0

24.0

0

0.0

Low

NR

44.0

16.0

14.0

40.0

16.0

0

0.0

Sandborn [35]

N Engl J Med

121.0

41.0

23.0

34.0

47.0

38.0

12

1.7

Low

110.0

40.0

24.0

28.0

44.0

40.0

4

2.2

119.0

33.0

16.0

37.0

9.0

38.0

6

3.6

116.0

40.0

26.0

35.0

54.0

46.0

5

2.9

Sandborn [36]

Gut

101.2

NR

86.5

24.3

70.3

45.9

0

0.0

Low

98.9

NR

67.0

18.0

44.0

56.0

0

0.0

Sandborn [37]

N Engl J Med

84.0

36.0

31.0

21.0

NR

22.0

7

2.1

Low

96.0

34.0

33.0

20.0

NR

23.0

3

0.9

Sandborn [38]

Gastroenterology

97.2

NR

NR

37.5

58.9

60.5

4

1.6

Low

102.0

NR

NR

32.5

63.0

56.9

5

2.0

Sandborn [39]

N Engl J Med

147.6

NR

NR

24.4

17.0

48.0

10

2.5

Low

148.8

NR

NR

22.7

18.2

55.3

8

6.1

Sandborn [40]

N Engl J Med

110.4

42.6

27.3

16.1

NR

34.7

45

4.7

Low

98.4

36.5

23.0

16.9

NR

30.4

9

6.1

Sandborn [41]

Gastroenterology

84.0

NR

NR

30.8

80.2

53.8

10

3.2

Low

82.8

NR

NR

33.3

80.1

56.4

3

1.9

Sands [42]

Inflamm Bowel Dis

150.3

NR

NR

50.0

46.0

27.0

0

0.0

Low

120.0

NR

NR

56.0

37.0

30.0

0

0.0

Schreiber [43]

Gastroenterology

99.6

36.1

NR

37.4

44.3

34.7

1

0.4

Low

95.4

37.0

NR

35.6

39.7

39.7

0

0.0

Schreiber [44]

N Engl J Med

108.0

30.0

30.0

27.0

NR

22.0

6

2.8

Low

84.0

35.0

36.0

25.0

NR

21.0

2

0.9

Targan [45]

Gastroenterology

121.4

NR

NR

37.0

49.0

42.0

1

0.4

Low

120.3

NR

NR

38.0

48.0

38.0

4

1.6

Abbreviations: CD Crohn’s Disease, UC ulcerative colitis, NR not reported, MTX methotrexate, AZA azathioprine, 6MP 6-mercaptopurine, MMF mycophenolate mofetil

ainclusive of active treatment period and follow-up

bincludes MTX, 6MP, AZA

&Step-up paradigm starting with prednisone then progressing to AZA

Fig. 2

Network of clinical trials of pharmacological treatment strategies for adults with inflammatory bowel disease (IBD). Each node in the network represents a treatment strategy and the connections signify pairwise treatment comparisons from the trials included

Table 2 provides the estimated odds of serious infection for all treatment strategies compared to placebo. Amongst all therapy contrasts, no statistically significantly increased odds of serious infection were discovered. However, the confidence intervals were extremely wide in many of the comparisons, and a clinically significant increase in infection risk could not be excluded. (Additional file 2: Table S2). Table 3 displays the estimates for selected therapeutic strategies compared to the anti-tumor necrosis factor (anti-TNF) biologics including infliximab, adalimumab, and certolizumab pegol. In the comparison of ustekinumab with certolizumab pegol there was found to be a lower odds of serious infection (OR 0.17, 95% CI 0.04–0.67). No statistically significant increased odds of serious infection were observed for any other treatment comparisons including those between the specific anti-TNFs agents (i.e. adalimumab vs. infliximab), as well as those between anti-TNF monotherapy and dual therapy with an immunomodulator (i.e. infliximab alone vs. infliximab + azathioprine/6MP) (Additional file 3: Table S3).
Table 2

Estimated odds of serious infection for treatment strategies compared to placebo

Treatment strategy

Comparator

Odds ratio

Standard error

95% Confidence interval

Infliximab

Placebo

1.36

0.45

0.57

3.27

Adalimumab

Placebo

0.77

0.36

0.38

1.56

Certolizumab pegol

Placebo

2.37

0.50

0.88

6.38

Natalizumab

Placebo

0.80

0.40

0.37

1.73

Ustekinumab

Placebo

0.40

0.49

0.16

1.05

Vedolizumab

Placebo

0.75

0.38

0.36

1.58

Golimumab

Placebo

1.71

0.67

0.46

6.31

Methotrexate

Placebo

0.52

1.28

0.04

6.34

Azathioprine/6MP

Placebo

1.43

0.61

0.43

4.76

Prednisone

Placebo

1.92

0.85

0.36

10.21

Budesonide

Placebo

1.99

1.65

0.08

50.97

Aminosalicylate

Placebo

1.37

1.40

0.09

21.47

Antibiotic

Placebo

1.01

1.07

0.12

8.34

Tacrolimus

Placebo

1.19

2.02

0.02

62.32

Methotrexate + prednisone

Placebo

2.94

1.45

0.17

50.23

Azathioprine/6MP + prednisone

Placebo

2.37

1.76

0.07

75.25

Aminosalicylate + prednisone

Placebo

7.32

2.41

0.06

832.34

Budesonide + prednisone

Placebo

1.89

2.18

0.03

135.88

MMF + prednisone

Placebo

4.14

2.07

0.07

241.50

Infliximab + azathioprine/6MP

Placebo

1.10

0.65

0.31

3.97

Azathioprine/6MP + aminosalicylate

Placebo

1.35

2.11

0.02

83.66

Natalizumab + inflximab

Placebo

0.71

2.06

0.01

40.65

Infliximab + azathioprine/6MP + prednisone

Placebo

0.32

2.33

0.00

30.40

Abbreviations: 6MP 6-mercaptopurine, MMF mycophenolate mofetil

Table 3

Estimated odds of serious infection for selecteda treatment strategies compared to anti-tumor necrosis factor biologics

Treatment strategy

Comparator

Odds ratio

Standard error

95% Confidence interval

Adalimumab

Infliximab

0.57

0.57

0.18

1.74

Certolizumab pegol

Infliximab

1.74

0.67

0.47

6.53

Natalizumab

Infliximab

0.58

0.60

0.18

1.88

Ustekinumab

Infliximab

0.30

0.66

0.08

1.08

Vedolizumab

Infliximab

0.55

0.58

0.18

1.74

Golimumab

Infliximab

1.26

0.80

0.26

6.05

Infliximab + azathioprine/6MP

Infliximab

0.81

0.50

0.30

2.17

Infliximab + azathioprine/6MP + prednisone

Infliximab

0.23

2.29

0.00

20.82

Certolizumab pegol

Adalimumab

3.08

0.62

0.91

10.37

Natalizumab

Adalimumab

1.03

0.54

0.36

2.94

Ustekinumab

Adalimumab

0.52

0.60

0.16

1.71

Vedolizumab

Adalimumab

0.98

0.52

0.35

2.71

Golimumab

Adalimumab

2.22

0.76

0.50

9.78

Natalizumab

Certolizumab pegol

0.34

0.64

0.10

1.18

Ustekinumab

Certolizumab pegol

0.17

0.70

0.04

0.67

Vedolizumab

Certolizumab pegol

0.32

0.63

0.09

1.09

Golimumab

Certolizumab pegol

0.72

0.84

0.14

3.71

Abbreviations: 6MP 6-mercaptopurine, MMF mycophenolate mofetil

aOther group comparisons can be found in Additional file 3: Table S3

Furthermore, no statistically significant increased odds of serious infection were found for any comparison in contrasting each therapy with the immunomodulators (azathioprine/6MP and methotrexate) or other commonly used therapies such as prednisone, budesonide, and tacrolimus (Table 4; Additional file 4: Table S4 and Additional file 5: Table S5). Similar findings were seen for the newer biologic pharmacotherapies including natalizumab, ustekinumab, and vedolizumab (Table 4; Additional file 6: Table S6). Lastly, no increased odds of serious of infection were found in comparisons of each included treatment strategy against other combinations of therapies such as methotrexate/prednisone or azathioprine/6MP + prednisone (Additional file 7: Table S7). However again, the confidence intervals were extremely wide in many of the comparisons, and a clinically significant increase in infection risk could not be excluded.
Table 4

Estimated odds of serious infection for selecteda treatment strategies of interest

Treatment strategy

Comparator

Odds ratio

Standard error

95% Confidence interval

Azathioprine/6MP

Methotrexate

2.75

1.42

0.17

44.07

Prednisone

Azathioprine/6MP

1.34

0.76

0.30

5.96

Infliximab + azathioprine/6MP

Azathioprine/6MP

0.77

0.50

0.29

2.06

Ustekinumab

Natalizumab

0.51

0.63

0.15

1.73

Vedolizumab

Natalizumab

0.95

0.55

0.32

2.76

Golimumab

Natalizumab

2.15

0.77

0.47

9.82

Vedolizumab

Ustekinumab

1.87

0.61

0.56

6.22

Golimumab

Ustekinumab

4.24

0.82

0.84

21.32

Golimumab

Vedolizumab

2.27

0.76

0.51

10.16

Abbreviations: 6MP 6-mercaptopurine

aOther group comparisons can be found in Additional files 1, 2, 3, 4, 5, 6, and 7

In the design-by-treatment interaction model, no evidence of inconsistency was found (chi^2 = 0.25, p = .99). Visual assessment of a comparison-adjusted funnel plot did not reveal any evidence of publication bias or other small study effects. Although the included studies were randomized, there were low rates of completed follow-up as well as selective cross over amongst therapy groups in many trials contributing to a high risk of bias. In addition, although the transitivity assumption was satisfied through randomization, there may remain differences in the study populations that modify the effect, thus, the overall quality of the body of evidence per the GRADE approach is low.

Discussion

In this network meta-analysis (NMA), we combined clinical trial data from thirty-eight published articles that included twenty-four different treatment strategies for IBD. These results summarize the risk of serious infection from available RCTs of commonly prescribed IBD pharmacotherapies. The study overcomes some of the limitations from previous studies by applying a universal definition for serious infection and examining large cohorts of treated patients from RCTs. Furthermore, the NMA technique allows for investigation of multiple therapies, including combinations of therapies, which have not been previously compared directly.

Our results show that no treatment strategy exhibits a higher odds of serious infection than another (including placebo), although in many cases the confidence intervals were wide, likely due to the small number of studies examining specific therapies available, and thus did not exclude a clinically significant increase in risk. Of particular interest, patients treated with dual immunosuppression with biologic medications and immunomodulators do not appear to be at higher risk of serious infection compared to those treated with biologic monotherapy, at least in the short-term. This lends additional support towards the safety of combination therapy as a viable treatment strategy, especially for those patients who are at high risk of antibody formation and subsequent loss of response from some biologic therapies. Our results are in contrast to those reported by Toruner et al. who showed an increased risk of opportunistic infections among patients treated with combination therapy in a retrospective case–control study [4]. This discrepancy is likely due to differences in study design and patient populations, as our meta-analysis is limited to patients enrolled in RCTs. First, the Toruner study could not assess disease severity; thus medication use could be a marker for disease severity rather than a true risk factor for infection. Second, patients who are eligible to be enrolled in an RCT are extensively screened for infection and other comorbidities prior to enrollment and followed more closely than in clinical practice. It is possible that this additional scrutiny both selected out patients who were more prone to infection and/or modified their risk for development of infection sometime during the trial period. Furthermore, the patients in the Toruner study were from one academic medical center and results may not be generalizable to other settings.

We found no evidence of a higher odds of serious infection from the newly available biologic therapies, such as vedolizumab and ustekinumab, compared to the anti-tumor necrosis factor (anti-TNF) biologic agents (or to one another). Given the growing number of patients who have lost response or who are intolerant to anti-TNFs, these findings are reassuring. Furthermore, we specifically looked at the comparison of those on triple immunosuppression (i.e. biologic + immunomodulator + steroid) versus those on combination therapy or biologic monotherapy, and similar results were found. Of note, we did observe a trend towards increased risk for serious infection with prednisone treatment, either as monotherapy or combined with other therapies. This trend was not statistically significant in any of the comparisons; however it is consistent with the existing evidence of the association of prolonged corticosteroid use and infection [4].

Previous estimates of the risk of serious infection related to IBD therapy vary widely, and the absolute risk is difficult to quantify. The SONIC trial assessed the relative risk of serious infection from azathioprine alone, infliximab alone, and azathioprine and infliximab together (combination therapy), and the authors found no statistically significant differences among the groups [5]. In addition, the absolute risk of serious infection was low in each group: azathioprine (5.6%), infliximab (4.9%), and combination therapy (3.9%) over a mean follow-up of 125.7 patient-years [5]. In contrast, a case control study at the Mayo Clinic found an increased risk of serious infection from combination therapy compared to infliximab monotherapy, as well as an increased odds of serious infection from infliximab, corticosteroids, and azathioprine/6MP alone compared to no medication [4]. Although these two well-known studies have conflicting results, the differences have been explained as likely due to the different patient populations [55]. Crohn’s disease (CD) is associated with more disease related infectious complications (e.g. abscesses) than ulcerative colitis (UC), but it is unclear if the risk of infectious complications differs between CD and UC. Our study, like many, did not examine CD and UC separately as we combined the two conditions in order to maximize the number of patients available for the analysis. In addition, the two conditions are often difficult to distinguish and there is significant overlap between the treatment paradigms.

In a recently published update to the ENCORE registry study, D’Haens et al. report an increased risk of serious infection among CD patients treated with infliximab compared to other IBD therapies [56]. Although the relative risk of serious infection was higher among those treated with infliximab or combination therapy, the absolute risk of infection remained low. The differences again are likely due to differing patient populations and our examination of CD and UC combined. Our results are comparable to the existing literature, in particular the SONIC trial, and suggest that the shorter-term risk of serious infection from IBD pharmacotherapy is low.

Our findings do have some limitations. First, we only included data from RCTs due to the added heterogeneity non-randomized studies would contribute to the analysis, as well as the desire to preserve the benefits of randomization in our analysis. This limits the external validity and representativeness of our findings, especially given the strict entry criteria for these trials. Patients with comorbidities or other characteristics excluded from these studies may be at higher risk of serious infections from IBD pharmacotherapy than those included in our study populations. Second, RCTs are not specifically designed or powered to investigate adverse events such as serious infections; thus we may underestimate the true association of these therapies with serious infection, a limitation that is not overcome by pooling evidence in a meta-analysis. Third, there was variable length of treatment and follow up among the included studies, which may underestimate the risk of serious infection. Many of the included trials had short follow-up duration and did not include details on the time to development of the infections, so longer-term risk of these therapies were not quantified. In a recently published article, the median time to the development of active tuberculosis after initiation of an anti-TNF was approximately three months, which lends support to the possibility that the true risk of serious infection could be underestimated in published RCTs; however the average duration of the RCTs included in this meta-analysis was 37 weeks, thus we expect that the included studies would have detected a large proportion of cases of tuberculosis [57]. However, this does not exclude the possibility that other serious infections with longer time to development were underreported. Fourth, the direct estimates for some therapeutic strategies are based on a single study due to the lack of available trial data. Fifth, RCTs investigating the newer biologics (e.g. vedolizumab, ustekinumab) have been published since the last literature search and are not included in this meta-analysis, which may influence our results. Lastly, traditional limitations of meta-analyses due to variations in the treatment regimens, in the study populations, and in the conduct of the individual trials may bias our estimates, the direction of which is indeterminable.

Despite these limitations, this study provides crucial information regarding one of the most clinically significant risks of interest associated with IBD pharmacotherapy. Our findings are robust in terms of the low estimate of inconsistency for our model and the completeness of the literature search of studies for inclusion. As additional data becomes available regarding IBD therapies, this information can be added to the network to increase our confidence in the estimates.

Conclusions

Our results add to the body of evidence regarding risks and benefits of IBD pharmacotherapy, and suggest that commonly used therapies are not associated with increased risk of serious infections in the first several months of treatment, although confidence intervals were wide for many comparisons; thus a clinically significant difference cannot be excluded. Further, long-term studies using larger cohorts will supplement these findings and increase the generalizability of these results.

Abbreviations

IBD: 

Inflammatory bowel disease

NMA: 

Network meta-analysis

RCT: 

Randomized controlled trial

WHO: 

World Health Organization

OR: 

Odds ratio

SE: 

Standard error

MTX: 

Methotrexate

6MP: 

6-mercaptopurine

anti-TNF: 

Anti-tumor necrosis factor

PRISMA: 

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Declarations

Funding

None.

Availability of data and materials

The datasets during and/or analyzed during the current study available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

CLW-formulation and study design; data assemblage; data analysis and interpretation; manuscript writing and revision of final manuscript; approval of final manuscript. CWK-formulation and study design; data analysis and interpretation; manuscript writing and revision of final manuscript; approval of final manuscript. KCS-formulation and study design; data assemblage; data analysis and interpretation; approval of final manuscript. DG-formulation and study design; approval of final manuscript. TAT-formulation and study design; approval of final manuscript. BD-formulation and study design; data analysis and interpretation; approval of final manuscript.

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Authors’ Affiliations

(1)
Department of Health Services, School of Public Health, University of Washington
(2)
Division of Gastroenterology, Department of Medicine, University of Washington
(3)
Department of Pharmacy, School of Pharmacy, University of Washington
(4)
Department of Biostatistics, School of Public Health, University of Washington

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