In the standard model for randomized clinical trials, patients are allocated on an equal, or 1:1, basis between two treatment arms. This means that at the conclusion of patient enrollment, there should be roughly equal numbers of patients receiving the new experimental treatment as those receiving the standard treatment or placebo. This 1:1 allocation ratio is the most efficient from a statistical perspective, since it requires the fewest number of patient-subjects to achieve a given level of statistical power.
However, many recent late-phase trials of neurological interventions have randomized their participants in an unequal ratio, e.g., on a 2:1 or 3:1 basis. In the case of 2:1 allocation, this means that there are twice as many patient-subjects receiving the new (and unproven) treatment as those receiving the standard or placebo. This practice is typically justified by the assumption that it is easier to enroll patient-subjects in a trial if they believe they are more likely to receive the new/active treatment.
In an article from this month’s issue of Neurology, Jonathan and I present three arguments for why investigators and oversight boards should be wary of unequal allocation. Specifically, we argue that the practice (1) leverages patient therapeutic misconceptions; (2) potentially interacts with blinding and thereby undermines a study’s internal validity; and (3) fails to minimize overall patient burden by introducing unnecessary inefficiencies into the research enterprise. Although these reasons do not universally rule-out the practice–and indeed we acknowledge some circumstances under which unequal allocation is still desirable–they are sufficient to demand a more compelling justification for its use.
The point about inefficiency reflects a trend in Jonathan’s and my work–elucidating the consequences for research ethics when we look across a series of trials, instead of just within one protocol. So to drive this point home here, consider that the rate of successful translation in neurology is estimated at around 10%. This means that for every 10 drugs that enter the clinical pipeline, only 1 will ever be shown effective. Given the limited pool of human and material resources available for research and the fact that a 2:1 allocation ratio typically requires 12% more patients to achieve a given level of statistical power, this increased sample size and cost on a per trial basis may mean that we use up our testing resources before we ever find that 1 effective drug.
BibTeX
@Manual{stream2014-468, title = {The Ethics of Unequal Allocation}, journal = {STREAM research}, author = {Spencer Phillips Hey}, address = {Montreal, Canada}, date = 2014, month = jan, day = 6, url = {http://www.translationalethics.com/2014/01/06/unequal-allocation/} }
MLA
Spencer Phillips Hey. "The Ethics of Unequal Allocation" Web blog post. STREAM research. 06 Jan 2014. Web. 14 Oct 2024. <http://www.translationalethics.com/2014/01/06/unequal-allocation/>
APA
Spencer Phillips Hey. (2014, Jan 06). The Ethics of Unequal Allocation [Web log post]. Retrieved from http://www.translationalethics.com/2014/01/06/unequal-allocation/