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Regulatory authorities make difficult risk-benefit decisions when approving new drugs. Food and Drug Administration (FDA) advisory committees and reviewers must consider a complex body of evidence, including efficacy and safety results of trials, disease epidemiology, potential side effects, and patients' needs. However, this menu of information is not usually presented in a consistent and integrated framework. The members of an FDA review panel vote with some unobserved, implicit weighting of the evidence. This paper argues that outcomes research tools for modeling long-term health outcomes, measuring health preferences, and establishing the value of additional information could provide a more structured, transparent, and quantitative process of assessing risk-benefit balance.
Garrison et al. (Tue,) studied this question.