Should benefit–risk assessment have its own drug “label”?

Figures & data

Table 1 Suppose evidence is being evaluated regarding a weight loss drug that confers a clinically significant benefit in 20% of patients treated but yields a life-threatening harm in 0.2% of patients treated. Using Incremental Net Health Benefit to infer that one patient harmed would offset at least 100 patients benefitted and assuming that the harm has a baseline frequency of 0.1%, any study with an n between 186 and 12,340 would have sufficient power to detect the benefit, yet would have insufficient power to detect the harm. Consequently, a label designating proof that “benefits exceed harms” could only be justified based on data well beyond those demonstrating benefits or supporting regulatory approval

n (both arms)	FDA approval?	Sufficient power to detect benefit?	Sufficient power to detect harms?	Sufficient power to detect harms offsetting benefit?
n < 186	No	No	No	No
186 ≤ n < 1800	No	Yes	No	No
1800 ≤ n < 12,340	Yes	Yes	No	No
n > 12,340	Yes	Yes	Yes	Yes

Abbreviation: n, number.

Figure 1 Language that could be included as part of a post-marketing “benefits exceed harms” label. Prior to the issuing of this label ([A] possible lay explanation), data may have been consistent with benefits exceeding harms, but not robust enough to constitute proof. Issuing the “benefits exceed harms” label ([B] possible lay explanation) would designate that sufficient evidence had accumulated to allow detection of harms that could offset known benefits and, consequently, proof that benefits exceed harms. This is a far higher evidence standard for benefit–risk assessment than is currently required for marketing approval, and is more akin to the current evidence standard for effectiveness.