The Role of Pharmacovigilance Database in Identifying Antibiotic Resistance and Inappropriate Use: An Analysis of VigiBase Reports From Lower-Middle-Income Countries.

Abstract

Background: Digital databases such as pharmacovigilance (PV) databases could provide unique opportunities to monitor trends in suspected antibiotic resistance, ineffectiveness, and misuse, extending beyond their traditional role of tracking adverse drug reactions (ADRs). This approach is potentially valuable globally but particularly advantageous in lower-middle-income countries (LMICs) where formal resistance surveillance systems are often insufficiently developed. Leveraging PV data could help generate early signals of resistance and inappropriate antibiotic use and support antimicrobial stewardship in resource-constrained settings.

Objectives: To explore the potential use of PV databases in monitoring suspected antibiotic resistance trends and inappropriate use in LMICs.

Methods: A retrospective cross-sectional study was conducted using VigiBase. Data were extracted in October 2024 from inception to January 1, 2024. Reports involving antibacterials for systemic use, Anatomical Therapeutic Chemical (ATC) codes J01 and J04 from LMICs were included. Selected Medical Dictionary for Regulatory Activities (MedDRA) preferred terms were mapped according to RIOLE classification to the "resistance," "ineffectiveness," "off-label use," and "error" categories to identify reporting patterns. Descriptive statistics were used to summarize reports' characteristics, and associations between categorical variables were examined using chi-squared tests.

Results: A total of 1570 ICSRs from 37 LMICs were identified, yielding 2958 drug-adverse event pairs, with reporting increasing markedly after 2016. The "off-label use" (38.6%) and "ineffectiveness" (37.0%) were the dominant RIOLE categories, driven mainly by the preferred terms (PTs) of Off-label use (795; 26.4%) and Drug ineffective (751; 25.4%). Resistance-related PTs accounted for 12.7% of pairs, most frequently Drug resistance (210; 7.0%) and Pathogen resistance (132; 4.5%), while "error" category (11.7%) was led by Product use issue (60; 2.0%) and Medication error (44; 1.5%). Watch antibiotics predominated, especially azithromycin, ceftriaxone, and meropenem, with significant associations observed between RIOLE categories and age, reporter type, ATC class, reaction outcome, AWaRe category, and WHO region.

Conclusions: These findings demonstrate that PV databases can provide valuable insights into suspected antibiotic resistance and inappropriate use patterns in LMICs, supporting their potential role as additional data sources in antimicrobial stewardship.