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Disproportionality analysis of infection associated with antidiabetic drug use patterns
Disproportionality analysis of infection associated with antidiabetic drug use patterns
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Disproportionality analysis of infection associated with antidiabetic drug use patterns
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Disproportionality analysis of infection associated with antidiabetic drug use patterns
Disproportionality analysis of infection associated with antidiabetic drug use patterns

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Disproportionality analysis of infection associated with antidiabetic drug use patterns
Disproportionality analysis of infection associated with antidiabetic drug use patterns
Journal Article

Disproportionality analysis of infection associated with antidiabetic drug use patterns

2025
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Overview
While various antidiabetic drug classes are associated with differing infection risks, comprehensive evidence on infection risk across multidrug regimens remains limited. Therefore, this study aims to investigate the pharmacovigilance signal between antidiabetic drug use and infection risk, considering the number and patterns of drug use. This study evaluated the pharmacovigilance signal between antidiabetic drug use and infection utilizing the global pharmacovigilance database. To account for adverse events from multiple drug use, we restructured the database at the individual level using a unique demographic identifier, allowing assessment of infection risk by drug combination and count. Antidiabetic drugs include metformin, sulfonylureas, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), sodium-glucose cotransporter-2 (SGLT2) inhibitors, thiazolidinediones, alpha-glucosidase inhibitors, and insulin, with infections categorized by the system. The pharmacovigilance signal of adverse drug reactions was estimated using adjusted reporting odds ratios (aRORs) with 95% confidence intervals (CIs) through multivariable logistic regression. SGLT2 inhibitor users reported the highest frequency of infections ( n  = 13,570), followed by insulin ( n  = 11,322) and GLP-1 RAs ( n  = 5966). When analyzing only monotherapy, excluding combination use, urinary tract infections were significantly linked solely to SGLT2 inhibitors (aROR, 10.41 [95% CI, 9.76–11.09]), while hepatobiliary and pancreatic infections were associated with DPP-4 inhibitors (aROR, 1.72 [95% CI, 1.28–2.31]), with no significant pharmacovigilance signal observed for other drug classes. Compared to monotherapy, combination therapy with two drugs (aROR, 1.24 [95% CI, 1.20–1.29]) or three or more drugs (aROR, 1.42 [95% CI, 1.13–1.79]) was associated with infection. Although the results from disproportionality analysis did not indicate causal relationship, our findings indicate that infection types vary between monotherapy and combination therapy, highlighting the need for further investigation into these pharmacovigilance signal due to the increased susceptibility of individuals with diabetes.