Comparative Study Designs: Claiming Superiority, Equivalence and Non-inferiority—A Few Considerations & Practical Approaches
This is a complex area, and we recommend downloading our freely available 1-page summary to help assess issues with equivalence and non-inferiority trials. Here is a short sampling of some of the problems in these designs: lack of sufficient evidence confirming efficacy of referent treatment, (“referent” refers to the comparator treatment); study not sufficiently similar to referent study; inappropriate Deltas (meaning the margin established for equivalence or non-inferiority); or significant biases or analysis methods that would tend to diminish an effect size and “favor” no difference between groups (e.g., conservative application of ITT analysis, insufficient power, etc.), thus pushing toward non-inferiority or equivalence.
However, we do want to say a few more things about non-inferiority trials based on some recent questions and readings.
Is it acceptable to claim superiority in a non-inferiority trial? Yes. The Food and Drug Administration (FDA) and the European Medicines Agency (EMA), among others, including ourselves, all agree that declaring superiority in a non-inferiority trial is acceptable. What’s more, there is agreement that multiplicity adjusting does not need to be done when first testing for non-inferiority and then superiority.
See Delfini Recommended Reading: Included here is a nice article by Steve Snapinn. Snappin even recommends that “…most, if not all, active-controlled clinical trial protocols should define a noninferiority margin and include a noninferiority hypothesis.” We agree. Clinical trials are expensive to do, take time, have opportunity costs, and—most importantly—are of impact on the lives of the human subjects who engage in them. This is a smart procedure that costs nothing especially as multiplicity adjusting is not needed.
What does matter is having an appropriate population for doing a superiority analysis. For superiority, in studies with dichotomous variables, the population should be Intention-to-Treat (ITT) with an appropriate imputation method that does not favor the intervention under study. In studies with time-to-event outcomes, the population should be based on the ITT principle (meaning all randomized patients should be used in the analysis by the group to which they were randomized) with unbiased censoring rules.
Confidence intervals (CIs) should be evaluated to determine superiority. Some evaluators seem to suggest that superiority can be declared only if the CIs are wholly above the Delta. Schumi et al. express their opinion that you can declare superiority if the confidence interval for the new treatment is above the line of no difference (i.e.., is statistically significant). They state, “The calculated CI does not know whether its purpose is to judge superiority or non-inferiority. If it sits wholly above zero [or 1, depending upon the measure of outcome], then it has shown superiority.” EMA would seem to agree. We agree as well. If one wishes to take a more conservative approach, one method we recommend is to judge whether the Delta seems clinically reasonable (you should always do this) and if not, establishing your own through clinical judgment. Then determine if the entire CI meets or exceeds what you deem to be clinically meaningful. To us, this method satisfies both approaches and makes practical and clinical sense.
Is it acceptable to claim non-inferiority trial superiority? It depends. This area is controversial with some saying no and some saying it depends. However, there is agreement amongst those on the “it depends” side that it generally should not be done due to validity issues as described above.
US Department of Health and Human Services, Food and Drug Administration: Guidance for Industry Non-Inferiority Clinical Trials (DRAFT). 2010.
European Agency for the Evaluation of Medicinal Products Committee for Proprietary Medicinal Products (CPMP): Points to Consider on Switching Between Superiority and Non-Inferiority. 2000. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2014556/