Drug vs Class-Specific Black Box Warnings: Does One Bad Drug Spoil the Bunch?

ArticleinJournal of General Internal Medicine 26(6):570-2 · April 2011with9 Reads
DOI: 10.1007/s11606-011-1714-9 · Source: PubMed
Abstract
Since safety concerns regarding prescription drugs are often discovered only after a medicine has been approved and released on the market, FDA regulatory advisories serve as an important means of communicating risk information to providers and to the general public. Although there are a variety of methods that the FDA uses to communicate such information, black box warnings are reserved for those deemed of highest public health importance. In many cases, risk information may be available for only select drugs within a therapeutic class, and thus the Agency often has to decide how broadly an advisory shoul db e applied when faced with incomplete information. Should a warning derived from data about a single agent be similarly applied across drugs within the same chemical class or across agents with similar pharmacologic effects? Why or why not? What factors should guide this decision? As with many decisions that the Agency makes, this deliberation can be complex, since it requires the combination of facts and judgments in the setting of incomplete scientific information. To complicate matters further, advisories focused on a single agent may have substantially different effects than advisories focused on an entire therapeutic class. For example, applying an advisory to a single member of a class may erroneously suggest superior safety of other members of the class in the absence of evidence to the contrary, and may also erode a particular agent’s market share and thus be met with resistance by industry stakeholders. The lack of specificity of a class-wide warning may blunt the impact of an advisory. 1 Too many advisories may lead to “alert fatigue.” Poorly worded or framed advisories may increase their spillover to untargeted populations. Indeed, as the history of risk communication has shown us, poorly managed messages about risks can become risks themselves. 2,3
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