Comparison of safety profiles for dapagliflozin based on EMA and FDA safety issues: Challenges and future of post-marketing surveillance in Korea

Abstract

Europe, the United States (U.S), and Korea each maintain post-marketing surveillance (PMS) systems to monitor rare or unexpected adverse events. Korea's PMS mainly involves a re-examination system to identify new adverse events not seen in pre-market trials during the early stages of post-marketing drug use, along with the risk management plan (RMP), a comprehensive strategy using methods like signal detection to regularly assess safety and benefit-risk throughout the drug's lifecycle. This study compares the post-marketing safety issues associated with dapagliflozin as identified by the European Medicines Agency (EMA), the U.S Food and Drug Administration (FDA), and in Korea. To identify these safety issues, we reviewed the safety concerns listed in the European Union RMP (EU-RMP), adverse events noted in the Warnings and Precautions section of the U.S FDA drug label, and use-result surveillance results detailed in the Korean Ministry of Food and Drug Safety drug label. Additionally, we used Korean Adverse Event Reporting System (KAERS) data to detect safety signals. We manually matched and compared safety issues identified by the EMA and FDA with those recognized in Korea. For safety issues unique to Korea, we compared KAERS signals with the results from use-result surveillance. We compared 17 EMA/FDA safety issues with 38 KAERS signals and 231 results from use-result surveillance. While there was a significant concordance (71%) between the safety issues identified by the EMA/FDA and those in Korea, Korean safety issues had limitations in capturing long-term outcomes and laboratory results. Some safety issues that were initially recognized in the EU-RMP and FDA drug labels were no longer found in the latest documents. To enhance PMS in Korea, it is necessary to establish more specific laws and regulations and develop detailed guidelines that utilize a variety of real-world data and research methodologies to continuously assess causality throughout the product lifecycle.