Automatic signal extraction prioritizing and filtering approaches in detecting post-marketing cardiovascular events associated with targeted cancer drugs from the FDA Adverse Event Reporting System (FAERS)

摘要

ObjectiveTargeted drugs dramatically improve the treatment outcomes in cancer patients; however, these innovative drugs are often associated with unexpectedly high cardiovascular toxicity. Currently, cardiovascular safety represents both a challenging issue for drug developers, regulators, researchers, and clinicians and a concern for patients. While FDA drug labels have captured many of these events, spontaneous reporting systems are a main source for post-marketing drug safety surveillance in ‘real-world’ (outside of clinical trials) cancer patients. In this study, we present approaches to extracting, prioritizing, filtering, and confirming cardiovascular events associated with targeted cancer drugs from the FDA Adverse Event Reporting System (FAERS).