Consensus clustering for case series identification and adverse event profiles in pharmacovigilance

作者：

Highlights：

• Cluster analysis can enable data-driven discovery in pharmacovigilance.

• It may help identify adverse drug reactions despite differences in manifestation.

• Consensus clustering can improve stability and clinical coherence of clusters.

• Empirical Bayes shrinkage can improve stability and likelihood of clusters.

摘要

•Cluster analysis can enable data-driven discovery in pharmacovigilance.•It may help identify adverse drug reactions despite differences in manifestation.•Consensus clustering can improve stability and clinical coherence of clusters.•Empirical Bayes shrinkage can improve stability and likelihood of clusters.

论文关键词：Cluster analysis,Methods,Pharmacovigilance,Adverse drug reaction reporting systems

论文评审过程：Received 29 May 2020, Revised 17 May 2021, Accepted 18 October 2021, Available online 22 October 2021, Version of Record 12 November 2021.

论文官网地址：https://doi.org/10.1016/j.artmed.2021.102199