Abstract
ObjectivePost-marketing drug surveillance is critical for strengthening pharmacovigilance in low- and middle-income settings. This study provides the first class-level pharmacovigilance analysis from a South Asian tertiary hospital, generating safety signals across 84 drug subclasses and evaluating concordance between Proportional Reporting Ratio (PRR) and Reporting Odds Ratio (ROR) methods.MethodsWe conducted a retrospective cross-sectional analysis of electronic health records (2018–2022), comprising 718,088 drug administration events. Adverse drug reactions (ADRs) were identified using ICD-9-CM/ICD-10-CM codes. Disproportionality analyses using PRR and ROR were applied to each subclass.ResultsPRR identified positive signals in 5 subclasses, while ROR identified 7. The seven high-risk subclasses included antitubercular agents (PRR 3.24; ROR 4.14), anesthetic muscle relaxants (2.44; 2.84), aminoglycosides (2.24; 2.55), immunosuppressants (2.19; 2.47), neurologic sedatives (2.06; 2.29), antineoplastic cytotoxic agents (1.95; 2.15), and general anesthetic agents (1.88; 2.06). Concordance between PRR and ROR was high (96.4% agreement; κ ≈ 0.80; McNemar p = 0.48). Signal strength correlated inversely with overall drug exposure (ρ = −0.34).ConclusionThis analysis establishes baseline class-level risk estimates in a developing pharmacovigilance environment, identifies disproportionately high-risk drug classes, and supports the robustness of PRR and ROR as complementary screening tools for regional drug safety monitoring.
| Original language | English (US) |
|---|---|
| Article number | 100711 |
| Journal | Exploratory Research in Clinical and Social Pharmacy |
| Volume | 21 |
| DOIs | |
| Publication status | Published - Mar 2026 |
Keywords
- Adverse drug reactions
- Disproportionality analysis
- Drug safety
- Pharmacovigilance
- Signal detection algorithms
- South Asia
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