A Network Analysis of Drug Combinations Associated with Acute Generalized Exanthematous Pustulosis (AGEP)

Martinez-De la Torre, Adrian ; Weenen, Eva van ; Kraus, Mathias ; Weiler, Stefan; Feuerriegel, Stefan und Burden, Andrea M. (2021): A Network Analysis of Drug Combinations Associated with Acute Generalized Exanthematous Pustulosis (AGEP). In: Journal of Clinical Medicine, Bd. 10, Nr. 19, 4486

Abstract

Acute generalized exanthematous pustulosis (AGEP) is a rare skin adverse drug reaction. The pathophysiology and causative drugs associated with AGEP are poorly understood, with the majority of studies in AGEP focusing on a single-drug-outcome association. We therefore aimed to explore and characterize frequently reported drug combinations associated with AGEP using the WHO pharmacovigilance database VigiBase. In this explorative cross-sectional study of a pharmacovigilance database using a data-driven approach, we assessed individual case safety reports (ICSR) with two or more drugs reported to VigiBase. A total of 2649 ICSRs reported two or more drugs. Cardiovascular drugs, including antithrombotics and beta-blockers, were frequently reported in combination with other drugs, particularly antibiotics. The drug pair of amoxicillin and furosemide was reported in 57 ICSRs (2.2%), with an O/E ratio of 1.3, and the combination of bisoprolol and furosemide was recorded 44 times (1.7%), with an O/E ratio of 5.5. The network analysis identified 10 different communities of varying sizes. The largest cluster primarily consisted of cardiovascular drugs. This data-driven and exploratory study provides the largest real-world assessment of drugs associated with AGEP to date. The results identify a high frequency of cardiovascular drugs, particularly used in combination with antibiotics.

• Dokumententyp: Zeitschriftenartikel
• Keywords: Artificial Intelligence, AI, Künstliche Intelligenz, KI
• Fakultät: Betriebswirtschaft > Institute of Artificial Intelligence (AI) in Management
• Themengebiete: 000 Informatik, Informationswissenschaft, allgemeine Werke > 000 Informatik, Wissen, Systeme
• ISSN: 2077-0383
• Sprache: Englisch