Pharmacoepidemiol Risk Manage.  2024 Mar;16(1):29-39. 10.56142/perm.24.0001.

Identifying Factors Associated with Spontaneous Reporting of Statin-Associated Muscle Symptoms Using Machine Learning-Based Cluster Analysis

Affiliations
  • 1College of Pharmacy, Chung-Ang University, Seoul, Korea

Abstract


Objective
We aimed to identify factors associated with adverse event (AE) reports in statin-associated muscle symptoms (SAMS) using hierarchical clustering of patients in the Korea Institute of Drug Safety and Risk Management - Korea Adverse Event Reporting System database (KIDS-KAERS DB) (2105A0027).
Methods
To explore the characteristics and risk factors of SAMS reports, we analysed the KIDSKAERS DB from 2016 to 2020. We included reports with a causality category level of “possible” or higher. Hierarchical clustering analysis was used to identify distinctive patterns within the dataset, with a particular focus on variables such as sex, age, statin type, contraindicated drugs and concomitant drugs. The reporting characteristics were described according to the cluster.
Results
Four clusters of AE reports were distinguished by hierarchical clustering: atorvastatin- and rosuvastatinassociated AE (cluster 1), pitavastatin- and simvastatin-associated AE (cluster 2), rosuvastatin-associated AE (cluster 3), and atorvastatin-associated AE (cluster 4). Cluster 1 had a relatively higher proportion of men (57 cases, 50.9%) and a higher mean age (64.8 years) than the other clusters. Concomitant drug use was more common in cluster 1 (56 cases, 50.0%) than in other clusters (33.5%–46.2%), and all serious AEs were observed in cluster 1.
Conclusion
Using hierarchical clustering, we found four distinct clusters based on SAMS report characteristics. Our findings further emphasize that patients prescribed statins, especially elderly male patients taking rosuvastatin and atorvastatin concomitantly with other medications, should be closely monitored for the development of rhabdomyolysis.

Keyword

Hydroxymethylglutaryl-CoA reductase inhibitors; Adverse drug reactions; Cluster analysis
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