Trials that estimate treatment effects that exclude any patient-important superiority of interventions under evaluation. Equivalence trials require...
Continue reading

Trials that estimate treatment effects that exclude any patient-important superiority of interventions under evaluation. Equivalence trials require a priori definition of the smallest difference in outcomes between these interventions that patients would consider large enough to justify a preference for the superior intervention (given the intervention's harms and burdens). The confidence interval for the estimated treatment effect at the end of the trial should exclude that difference for the authors to claim equivalence (i.e., the confidence limits should be closer to zero than the minimal patient-important difference). This level of precision often requires investigators to enroll large numbers of patients with large numbers of events. Equivalence trials are helpful when investigators want to see whether a cheaper, safer, simpler (or increasingly often, better method to generate income for the sponsor) intervention is neither better nor worse (in terms of efficacy) than a current intervention. Claims of equivalence are frequent when results are not significant, but one must be alert to whether the confidence intervals exclude differences between the interventions that are as large as or larger than those patients would consider important. If they do not, the trial is indeterminate rather than yielding equivalence.