Benefit–Risk Tradeoffs in Assessment of New Drugs and Devices
Author(s) -
Sanjay Kaul,
Norman Stockbridge,
Javed Butler
Publication year - 2020
Publication title -
circulation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.795
H-Index - 607
eISSN - 1524-4539
pISSN - 0009-7322
DOI - 10.1161/circulationaha.120.048933
Subject(s) - medicine , prasugrel , risk assessment , intensive care medicine , risk analysis (engineering) , risk management , clopidogrel , finance , computer security , aspirin , computer science , economics
Balancing benefits and risks is a complex task that poses a major challenge, both to the approval of new medicines and devices by regulatory authorities and in therapeutic decision-making in practice. Several analysis methods and visualization tools have been developed to help evaluate and communicate whether the benefit–risk profile is favorable or unfavorable. In this White Paper, we describe approaches to benefit–risk assessment using qualitative approaches such as the Benefit Risk Action Team framework developed by the Pharmaceutical Research and Manufacturers of America, and the Benefit–Risk Framework developed by the United States Food and Drug Administration; and quantitative approaches such as the numbers needed to treat for benefit and harm, the benefit–risk ratio, and Incremental Net Benefit. We give illustrative examples of benefit–risk evaluations using 4 treatment interventions including sodium glucose cotransporter 2 inhibitors in patients with type 2 diabetes; a direct antithrombin agent, dabigatran, for reducing stroke and systemic embolism in patients with nonvalvular atrial fibrillation; transcatheter aortic valve replacement in patients with symptomatic severe aortic valve stenosis; and antiplatelet agents vorapaxar and prasugrel for reducing cardiovascular events in patients at high cardiovascular risk. Regular applications of structured benefit–risk assessment, whether qualitative, quantitative, or both, enabled by easy-to-understand graphical presentations that capture uncertainties around the benefit–risk metric, may aid shared decision-making and enhance transparency of those decisions.
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