Abstract
OBJECTIVE: The clinical risk of cognitive disorders linked to various drugs is not well-defined. This study aimed to identify medications with notable signals for drug-related cognitive disorders and evaluate whether their US Food and Drug Administration (FDA)-approved labels include relevant safety warnings. METHODS: A retrospective disproportionality analysis using FDA Adverse Event Reporting System data (2004-2024) employed four algorithms-Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN) and Multi-Item Gamma Poisson Shrinker (MGPS)-for signal detection. To confirm the results, a cross-database consistency check was performed with the Japanese Adverse Drug Event Report (JADER) and World Health Organization (WHO) VigiAccess databases. RESULTS: An analysis of 41,775 reports on drug-related cognitive disorders found significant signals for 50 medications using four algorithms. Notably, 74% of these drugs, including finasteride, diltiazem, and carbidopa/levodopa, lacked cognitive disorder warnings in FDA labels. Reporting patterns were classified into early or random failure types. Subgroup analyses showed certain drugs were disproportionately reported in vulnerable groups, such as antiepileptics in children and neurologic agents in seniors. The U.S. had the most reports. Multivariate analysis identified 43 factors linked to higher reporting odds, including conditions like depression and the use of specific drugs. Cross-database validation confirmed consistent signals for 92% of primary drug-event pairs. CONCLUSION: This pharmacovigilance analysis uncovers significant, previously unrecognized signals of drug-related cognitive disorders in various medications, most lacking label warnings. These findings highlight the need for further research, potential label updates, and increased clinical awareness, particularly in high-risk groups. Importantly, these results indicate statistical associations, not causal links, between the drugs and cognitive disorders.