Real-World Data-Derived Pharmacovigilance on Drug-Induced Cognitive Impairment Utilizing a Nationwide Spontaneous Adverse Reporting System

Background and Objectives: Despite high incidences of cognitive impairment with aging, evidence on the prevalence and the seriousness of drug-induced cognitive impairment is limited. This study aims to evaluate the prevalence and the severity of drug-induced cognitive impairment and to investigate the clinical predictors of increased hospitalization risk from serious drug-induced cognitive impairment. Materials and Methods: Adverse drug events (ADEs) regarding drug-induced cognitive impairment reported to the Korean Adverse Event Reporting System Database (KAERS DB) from January 2012 to December 2021 were included (KIDS KAERS DB 2212A0073). The association between the etiologic classes and the reporting serious adverse events (SAEs) was evaluated using disproportionality analysis, and the effect was estimated with reporting odds ratio (ROR). Clinical predictors associated with increased risk of hospitalization from SAEs were identified via multivariate logistic analysis, and the effect was estimated with odds ratio (OR). Results: The most etiologic medication class for drug-induced cognitive impairment ADEs was analgesics, followed by sedative-hypnotics. Anticancer (ROR 57.105, 95% CI 15.174–214.909) and anti-Parkinson agents (ROR 4.057, 95% CI 1.121–14.688) were more likely to report serious drug-induced cognitive impairments. Male sex (OR 19.540, 95% CI 2.440–156.647) and cancer diagnosis (OR 18.115, 95% CI 3.246–101.101) are the major clinical predictors for increased risk of hospitalizations due to serious drug-induced cognitive impairment. Conclusions: This study highlights the significant prevalence and severity of drug-induced cognitive impairment with cancer diagnosis and anticancer agents. However, further large-scaled studies are required because of the potential underreporting of drug-induced cognitive impairments in real practice settings, which is further contributed to by the complexity of multiple contributing factors such as comorbidities.