Systematic Review and Meta-Analysis of Inflammatory Bowel Disease Adverse Events with Anti-Interleukin 17A Agents and Tumor Necrosis Factor Inhibitors in Rheumatic Disease and Skin Psoriasis

Abstract

Introduction: The aim of this work is to perform a systematic review and meta-analysis of anti-tumor necrosis factor (anti-TNF) and anti-interleukin-17 (anti-IL-17) trials for spondyloarthritis, psoriatic arthritis, and psoriasis comparing rates of inflammatory bowel disease (IBD) events compared to placebo. Methods: MEDLINE, EMBASE, and The Cochrane Library were searched for double-blind, randomized placebo-controlled anti-TNF and anti-IL-17 trials of included diseases. Inflammatory bowel disease events from the RCT period were pooled and meta-analyzed using statistical methods suitable for low-event-rate meta-analysis (Peto’s, Mantel–Haenszel, hypergeometric-normal model, and Shuster-Guo-Skyler). When observed data were insufficient, we performed an exploratory sensitivity analysis to compare methods. Results: We identified 9551 original papers, and included 96 publications: 65 anti-TNF and 31 anti-IL-17 trials, containing 21 new and 12 flare IBD events in 28,209 participants. New IBD on anti-IL-17 occurred 0.23/100 patient-years (PY) in psoriasis, 0.61/100 PY in PsA and 1.63/100 PY in spondyloarthritis, rates similar to observational cohorts, and less commonly on anti-TNF (0/100 PY, 0/100 PY, 0.32/100 PY, respectively). No evidence of difference between groups was found, with wide CI from many pooled counts of zero, especially in placebo arms. Conclusions: IBD events were rare, occurring at rates similar to biologic-naive groups. We could not find statistically significant differences in risk of new or recurrent IBD between treatment and control groups using selected meta-analytical methods for low event rate scenarios. Meta-analyses of this topic require more IBD events, ideally without pooling heterogeneous groups. Larger, thoroughly reported trials with systematic and detailed safety reporting are required to improve risk estimation and to make accurate inferences.