Infection profile of immune-modulatory drugs used in autoimmune diseases: analysis of summary of product characteristic data.

Objective: Serious infection remains a concern when prescribing immune-modulatory drugs for immune-mediated inflammatory diseases. The 'summary of product characteristics' (SmPCs) provide information on adverse events for example, infections, from clinical trials and postmarketing pharmacovigilance.This review aimed to compare infection frequency, site and type across immune-modulatory drugs, reported in SmPCs.

Methods: The Electronic Medicines Compendium was searched for commonly prescribed immune-modulatory drugs used for: rheumatoid arthritis, spondyloarthritis, connective tissue disease, autoimmune vasculitis, autoinflammatory syndromes, inflammatory bowel disease, psoriasis, multiple sclerosis and/or other rarer conditions.Information was extracted on infection frequency, site and organisms. Frequency was recorded as per the SmPCs: very common (≥1/10); common (≥1/100 to<1/10); uncommon (≥1/1,000 to<1/100); rare (≥1/10,000 to<1/1,000); very rare (<1/10 000).

Results: 39 drugs were included, across 20 indications: 9 conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs), 6 targeted synthetic DMARDs, 24 biologic (b)DMARDs.Twelve infection sites were recorded. Minimal/no site information was available for most csDMARDs, certolizumab pegol and rituximab. Upper respiratory tract was the most common site, especially with bDMARDs. Lower respiratory, ear/nose/throat and urinary tract infections were moderately common, with clustering within drug groups.Data for 27 pathogens were recorded, majority viruses, with herpes simplex and zoster and influenza most frequent. Variable/absent reporting was noted for opportunistic and certain high-prevalence infections for example, Epstein-Barr.

Conclusion: Our findings show differences between drugs and can aid treatment decisions alongside real-world safety data. However, data are likely skewed by trial selection criteria and varying number of trials per drug and highlight the need for robust postmarketing pharmacovigilance.