Real-World Data Mining for Signal Detection of Antipsychotics-Associated Adverse Events Using the Korea Adverse Event...

Area of Science:

• Pharmacovigilance
• Neuroscience
• Cardiology

Background:

• Traditional categorization of antipsychotics into FGAs and SGAs based on side effect profiles (EPS vs. cardiometabolic) is an oversimplification.
• SGAs possess D2 receptor antagonism, suggesting potential for extrapyramidal symptoms (EPSs).

Purpose of the Study:

• To investigate adverse drug event (ADE) signals for both FGAs and SGAs using the Korea Adverse Event Reporting System (KAERS) database.
• To analyze the distribution of ADEs between FGAs and SGAs, challenging binary classifications.

Main Methods:

• Utilized disproportionality analysis (PRR, ROR, IC) on KAERS data from January 2013 to December 2022.
• Analyzed 5249 relevant ADE reports after data cleaning and deduplication.

Main Results:

• Aripiprazole (SGA) showed significant signals for movement disorders, including EPSs, tremors, and akathisia.
• Quetiapine (SGA) exhibited signals for cardiovascular effects like increased blood pressure and tachyarrhythmia, alongside peripheral edema.
• Metabolic abnormalities (weight gain, increased appetite) were linked to four SGAs: aripiprazole, olanzapine, quetiapine, and risperidone.
• Movement disorder signals were not detected for FGAs, potentially due to limited reporting data.

Conclusions:

• The distribution of adverse drug events between FGAs and SGAs is not strictly binary.
• Aripiprazole, an SGA, is associated with extrapyramidal movement disorders.
• Four SGAs (aripiprazole, olanzapine, quetiapine, risperidone) are linked to metabolic side effects, and quetiapine to cardiovascular signals.