Scientific and ethical issues in equivalence trials.

ANY TESTING OF MEDICAL TREATMENTS IS AN EXERcise in comparison. In a typical clinical trial, 2 treatments are compared to determine which is better or if both are the same. Trials designed to address whether one treatment is better than the other may be called superiority trials, whereas those designed to show that 2 treatments are the same are called equivalence trials. However, the design of both types of trials should depend on the uncertainty principle—a fundamental ethical and scientific principle for conducting randomized controlled trials. The article by Staszewski et al in this issue of THE JOURNAL is a randomized controlled equivalence trial that compares a triple nucleoside regimen of abacavir-lamivudinezidovudine with a more conventional regimen of indinavirlamivudine-zidovudine in treatment-naive patients infected with human immunodeficiency virus (HIV). Although the authors conclude that these 2 regimens are equivalent in achieving the primary end point of reducing plasma HIV RNA levels to below 400 copies/mL, several factors make the interpretation of this study and other equivalence trials particularly difficult. In planning a clinical trial of a new intervention, 2 main issues must be addressed. The first is the fundamental ethical question of whether the use of the new intervention is justified. The second is the choice of the appropriate control group. Both issues are fundamentally related to the preexisting knowledge about the therapeutic value of the treatments to be compared. This is an important reason that clinical trials should be preceded by a systematic review to assess the status of this knowledge, and should be reported with a discussion of an updated review including the trial’s results. The trial would not be justified if one of the treatments to be assessed is known to be superior to the other. A clinical trial is only justified if the patient and clinician are not certain about which treatment to choose from the available options. If they are uncertain (indifferent) about the relative value of the treatments, it is time for a trial. This is not only because the trial will help resolve this uncertainty but also because it is the fairest way to choose the treatment for the patient. Patients enrolled in the study have a 50% chance of receiving the better treatment and the overwhelming weight of evidence is that they will fare better while participating in the trial (regardless of the treatment they are allocated to) than while outside of it. This realization forms a basis for the scientific and ethical underpinnings for the design and conduct of randomized trials, expressed in the term uncertainty principle, which states that a patient should be enrolled in a randomized controlled trial only if there is substantial uncertainty about which of the trial treatments would benefit the patient more. Basing trials on the uncertainty principle also addresses another important issue in the design of a clinical trial— the choice of an adequate comparator for the intervention under investigation. Studies in which the intervention and the control or comparison group are known in advance to be nonequivalent in their effects on the main outcomes of interest violate the uncertainty principle. Even if a study is properly reported, extra caution might be needed in its interpretation if the choice of the comparison treatment was not based on uncertainty about the relative value of the treatments being assessed. Uncertainty can have many grades ranging from simply not knowing to maximum uncertainty (also known as equipoise) about the relative benefits and harms of the treatment alternatives. The uncertainty might be in the mind of the patient, the clinician, or the community. Most clinical trials are assessments of superiority and start with the statement of a null hypothesis of no difference between 2 therapies. That is, prior research should not have proved a difference between the alternative treatments in the outcomes to be assessed. The trial is designed to reject the null hypothesis by showing that there is a difference between the treatments. Since the null hypothesis can never be proven, but only rejected, alternative hypotheses (ie, that one treatment is better) are not assessed directly, but are accepted if the probability that the observed results are