Evaluating "superiority", "equivalence" and "non-inferiority" in clinical trials

Abstract

Clinical studies are usually performed with the aim of justifying that a new treatment approach is "superior" to the common standard approach (active control) with respect to benefits. In a general sense, this justification is carried out on the basis of the "null hypothesis significance test" with the P value based on this test used for justification. Today, new drugs differ so little from existing ones that factors such as cost and side effects affect the choice of therapy, when the bioavailability of treatment methods are found equivalent. Therefore, the aim of comparative clinical trials has extended beyond showing that a treatment is "superior" and now attempts to show that new treatments are "equal" and "non-inferior" to existing treatments. New approaches have become necessary since the classical null hypothesis approach is insufficient to justify the use of new agents, especially in cases of "equivalence" and "non-inferiority". This new approach to justification makes use of the "clinical equivalence interval", which determines the limits of the differences between specific endpoints that can be regarded as clinically "equal" to the value that was pre-specified based on studies of established therapies. It also makes use of the quantitative-based "confidence intervals" as the criteria for statistical justification. Many analyses can be done confidently when these tools are applied and the data are interpreted correctly.

Figure 1

The statistical figuration of the evaluation for “superiority” using the approach of confidence intervals.

Figure 2

Confidence interval approach and evaluation of the equivalence with “Δ”.

Figure 3

Confidence interval approach and evaluation of the non-inferiority with “Δ”.