BioScience Trends. 2022;16(2):151-157. (DOI: 10.5582/bst.2022.01115)

Time to onset of drug-induced parkinsonism: Analysis using a large Japanese adverse event self-reporting database

Sato K, Niimi Y, Mano T, Iwata A, Iwatsubo T


SUMMARY

Whether there are differences in the time to onset of drug-induced parkinsonism (DIP) depending on the type of drugs causing DIP remains uncertain, so that question was investigated here using a large real-world database. Fourteen DIP-related drug categories were defined to perform a disproportionality analysis using a large Japanese pharmacovigilance database containing more than 600,000 self-reported adverse events (AEs) recorded between April 2004 and September 2021 to identify AEs indicating "parkinsonism" in association with the defined drug categories. The time from drug administration to the onset of DIP was comparatively analyzed. Results indicated that the median time to onset was shorter than 1 month in more than half of the cases of DIP; it was shortest with peripheral dopamine antagonists (median: 0.1 weeks), followed by benzodiazepine (median: 0.5 weeks), butyrophenone (median: 0.7 weeks), novel antidepressants (median: 2.5 weeks), atypical antipsychotics (median: 3.3 weeks), other antidepressants (e.g., lithium, median: 3.7 weeks), and benzamide (median: 4.5 weeks). In contrast, anti-dementia drugs, tricyclic antidepressants, and antiepileptic drugs resulted in a relatively longer time to onset (median: 9.9, 17.2, and 28.4 weeks, respectively). In addition, a maximum delay of even longer than 2 years was reported for benzamide (846 weeks), anti-Parkinsonism drugs (382 weeks), phenothiazine (232 weeks), atypical antipsychotics (167 weeks), anti-dementia drugs (161 weeks), and benzodiazepines (120 weeks). The current results suggested that the characteristics of the time to onset of DIP may substantially differ depending on the type of drug causing that DIP. This finding may help when diagnosing patients with parkinsonism.


KEYWORDS: drug-induced parkinsonism, real-world data, adverse events, pharmacovigilance

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