(N) Triazole Anti-fungals Associated with Acute Pancreatitis: A Disproportionality Analysis in a Spontaneous Reporting Database

Friday, August 26, 2022

8:00 AM – 6:00 PM CEST

Location: Hall E South

Publication Number: 304

Presenting Author(s)

Lipin Lukose, PharmD
– Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Udupi, Karnataka, India

Co-Author(s)

Aina M. Shaju, PharmD
– Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India
Mohammed Asif
– Scientist-C, Department of Microbiology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India
Subeesh Kulangara Viswam, MPharm
– Assistant Professor, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Udupi, Karnataka, India

Background: Triazole antifungals are used as a first-line treatment for many fungal infections but the association of triazole antifungals with acute pancreatitis is very scarce.

Objectives: To detect the possible safety signal of triazole antifungals associated with acute pancreatitis through disproportionality analysis in FDA Adverse Event Reporting System (FAERS) Database.

Methods: The case/non-case retrospective disproportionality analysis was performed in a publicly available FAERS database using Open Vigil 2.1(2004Q1-2021Q3). The preferred term used for the study was “Pancreatitis Acute” and the drugs included in the analysis were posaconazole, itraconazole, fluconazole, ketoconazole, voriconazole and clotrimazole. Proportional reporting ratio (PRR) and Reporting odds ratio (ROR) was used as the data mining algorithm for the analysis. A value of ROR-1.96SE>1 and PRR2 with an associated X2 value of 4 or more was considered as the threshold for a signal. In silico off-label target (OLT) prediction was done through four independent prediction tools which utilised the similarity ensemble approach.

Results: A total of 9095 reports of acute pancreatitis were found in the FAERS database, with 134 reports associated with triazole antifungals. Significant signals were obtained for posaconazole[(ROR 4.5(95%CI= 2.8-7.2) and PRR 4.5(2.8-7.2)], itraconazole [(ROR 2.2(1.4-3.8) and PRR 2.3(1.4-3.8)], fluconazole [(ROR 2.8 (2.2-3.6) and PRR 2.8(2.2-3.6)] and voriconazole [(ROR 2(1.4-2.9) and PRR 2(1.4-2.9)] associated acute pancreatitis. The observed association revealed that females had higher ROR value of 2.3, 2.1 and 1.3 times for itraconazole, fluconazole and posaconazole respectively. Five OLTs (ABCB1, CYP3A4, CYP2C8, CYP2C9, CYP2D6) related to the potential anti-fungals associated with pancreatitis were identified using the in-silico approach which was further validated through docking methods.

Conclusions: Our analyses of spontaneous reporting data identified signals for acute pancreatitis with posaconazole, itraconazole, fluconazole and voriconazole. More research with a superior epidemiological study design with a defined population is needed to validate these findings.