Strengths, weaknesses, and opportunities: three tales demonstrating the use, usefulness, and limitations of Canadian post-market data of adverse drug reactions in real-world settings

Abstract

Adverse drug reactions (ADRs) – unintended and harmful events potentially caused by medication use – are a significant concern in healthcare, impacting patient safety, clinical outcomes, and economic burden. Although accurately assessing the risk and economic impact of ADRs in real-world settings is of utmost importance, such efforts are often hindered by the availability and quality of post-market ADR data. This dissertation demonstrates the value of the Canada Vigilance Adverse Reaction (CVAR) database, a repository of Canadian post-market ADR reports maintained by Health Canada, as a potential source of decision-grade information on ADRs. It develops and applies a consistent methodology that can be replicated across different disease areas or specific drugs, leveraging the CVAR database. Through three dissertation projects, this dissertation highlights the strengths, weaknesses, and opportunities of using the CVAR database. In terms of strengths, Dissertation Project 1 illustrates that the CVAR database provides real-world insights into the risk of serious ADR outcomes associated with two brand-name drugs, Remicade and Humira. This project highlights that randomized controlled trials may not accurately reflect the true incidence of certain ADR outcomes in the real-world. Regarding weaknesses, Dissertation Project 2 demonstrates that the CVAR database may not always offer reliable real-world reflections for ADRs, particularly for drugs used to treat diseases with high reporting bias such drugs for mental health. For opportunities, Dissertation Project 3 showcases how ADR reports associated with infliximab and adalimumab in the CVAR databases can help identify potential risk signals for serious ADR outcomes. While analyses based solely on the CVAR database may not be sufficient to draw definitive conclusions, they provide a foundation for generating and testing hypotheses to better understand emerging ADR patterns. Despite limitations such as reporting bias and underreporting, leveraging post-market ADR data remains essential for enhancing drug safety and regulatory decision-making.