RESUMEN
BACKGROUND AND STUDY AIM: The study was designed to detect novel Adverse Events (AEs) of pantoprazole by disproportionality analysis in the FDA (Food and Drug Administration) database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Pantoprazole, the most commonly over-utilized Over The Counter (OTC) medication, was selected to assess any short-term or long-term AEs. The study aimed to analyze the novel adverse events of pantoprazole using the FAERS database. MATERIALS AND METHODS: A retrospective case/non-case disproportionality analysis was performed in the FAERS database. This study was based on AEs reported to FAERS from 2006Q1-2021Q3. Openvigil 2.1 was used for data extraction. Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Information Component (IC) were applied to measure the disproportionality in reporting. A value of ROR-1.96SE > 1, PRR ≥ 2, and IC-2SD > 0 were considered as the threshold for a positive signal. RESULTS: A total of 1050 reports of dyspepsia, 7248 reports of hypocalcemia and 995 reports of hyponatremia were identified. A potential positive signal for dyspepsia (ROR-1.96SE = 2.231, PRR = 2.359, IC-2SD = 1.13), hypocalcemia (4.961, 5.45, 2.23) and hyponatremia (3.948, 4.179, 1.92) were identified for pantoprazole. CONCLUSION: Data mining in the FAERS database produced three potential signals associated with pantoprazole. As a result, further clinical surveillance is needed to quantify and validate potential hazards associated with pantoprazole-related adverse events.
