Drug-induced gingival overgrowth: FAERS based real-world pharmacovigilance study and network pharmacology analysis

Drug-induced gingival overgrowth (DIGO) as an interdisciplinary clinical challenge, faces dual therapeutic barriers due to its unclear pathogenesis and high recurrence rate, forcing clinicians to balance therapeutic benefits against oral complications. Analyzing drug-adverse reaction links via real-world evidence can shift treatment from passive intervention to proactive prevention. This study aimed to identify DIGO-associated drugs using the US Food and Drug Association Adverse Event Reporting System (FAERS) data and to validate signals through pharmacology-guided multivariate logistic regression, thereby improving signal robustness and clinical interpretability.

FAERS data (2004Q1-2024Q4) were analyzed. Multiple disproportionality methods including reporting odds ratios (RORs), proportional reporting ratios (PRRs), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) were employed for signal detection, with Fisher's exact test and false discovery rate (FDR) correction applied to control for multiple testing. Positive signals were subsequently validated through multivariate logistic regression and time-to-onset (TTO) analysis. Network pharmacology incorporating Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses to delineate underlying molecular pathways.

Among 22,375,298 reports, 1,835 cases of gingival hyperplasia and 11,145 gingival lesions were identified. Bisphosphonates, alongside calcium-channel blockers (CCBs), immunosuppressants (IMMs), and antiepileptics (AEPs), showed significant associations (p < 0.0001). Zoledronic acid (ROR = 3.23, 95% CI: 2.24-4.67) and pamidronate (ROR = 5.33, 95% CI: 2.8-9.92) showed strong signals. TTO analysis indicated prolonged bisphosphonate use increased DIGO risk. Network analysis suggested possible involvement of Phosphatidylinositol 3-Kinase/A Kinase T (PI3K-AKT) and Mitogen-Activated Protein Kinase (MAPK).

CCBs carried the highest DIGO risk, followed by IMMs and AEPs. Bisphosphonates were associated with DIGO and may act through PI3K-AKT/MAPK pathways, providing a mechanistic hypothesis for clinical medication safety.