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. 2017 Apr 14;17:52. doi: 10.1186/s12876-017-0602-0

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

Chelle L Wheat 1,2,, Cynthia W Ko 2, Kindra Clark-Snustad 2, David Grembowski 1, Timothy A Thornton 4, Beth Devine 1,3
PMCID: PMC5391579  PMID: 28407755

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).

Electronic supplementary material

The online version of this article (doi:10.1186/s12876-017-0602-0) contains supplementary material, which is available to authorized users.

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.

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.

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.

Additional files

Additional file 1: Table S1. (30.3KB, docx)

Search Algorithms. (DOCX 30 kb)

Additional file 2: Table S2. (29.1KB, docx)

Estimated odds of serious infection for treatment strategies compared to aminosalicylates or antibiotics. (DOCX 29 kb)

Additional file 3: Table S3. (38.5KB, docx)

Estimated odds of serious infection for treatment strategies compared to anti-tumor necrosis factor biologics. (DOCX 38 kb)

Additional file 4: Table S4. (30.5KB, docx)

Estimated odds of serious infection for treatment strategies compared to Immunomodulators. (DOCX 30 kb)

Additional file 5: Table S5. (33.1KB, docx)

Estimated odds of serious infection for treatment strategies compared to other immunosuppressants. (DOCX 33 kb)

Additional file 6: Table S6. (35.7KB, docx)

Estimated odds of serious infection for treatment strategies compared to other biologics. (DOCX 35 kb)

Additional file 7: Table S7. (33KB, docx)

Estimated odds of serious infection for treatment strategies compared to combination therapies. (DOCX 33 kb)

Acknowledgments

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.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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

Contributor Information

Chelle L. Wheat, Phone: 206-310-5984, Email: wheatc@uw.edu

Cynthia W. Ko, Email: cynthiak@medicine.washington.edu

Kindra Clark-Snustad, Email: kclark-snustad@medicine.washington.edu.

David Grembowski, Email: grem@uw.edu.

Timothy A. Thornton, Email: tathornt@uw.edu

Beth Devine, Email: bdevine@uw.edu.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file 1: Table S1. (30.3KB, docx)

Search Algorithms. (DOCX 30 kb)

Additional file 2: Table S2. (29.1KB, docx)

Estimated odds of serious infection for treatment strategies compared to aminosalicylates or antibiotics. (DOCX 29 kb)

Additional file 3: Table S3. (38.5KB, docx)

Estimated odds of serious infection for treatment strategies compared to anti-tumor necrosis factor biologics. (DOCX 38 kb)

Additional file 4: Table S4. (30.5KB, docx)

Estimated odds of serious infection for treatment strategies compared to Immunomodulators. (DOCX 30 kb)

Additional file 5: Table S5. (33.1KB, docx)

Estimated odds of serious infection for treatment strategies compared to other immunosuppressants. (DOCX 33 kb)

Additional file 6: Table S6. (35.7KB, docx)

Estimated odds of serious infection for treatment strategies compared to other biologics. (DOCX 35 kb)

Additional file 7: Table S7. (33KB, docx)

Estimated odds of serious infection for treatment strategies compared to combination therapies. (DOCX 33 kb)

Data Availability Statement

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


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