The Noninferiority Margin

A more recent area of application for meta-analysis is in the choice of the noninferiority margin, A. As mentioned in Section 12.8, A is often chosen as some proportion of the established treatment effect (over placebo) and meta-analysis can be used to obtain an estimate of that treatment effect and an associated confidence interval. 

For the sake of this example, let us say that a decrease in mean efficacy of 3 mmHg in SBP is acceptable. (Please note again that this is a hypothetical example.) The resulting value of minus 3 mmHg yields the noninferiority margin. The trial is then conducted. The treatment effect is calculated, as in superiority trials and equivalence trials, as the difference between the treatment group means. 

As in the case of equivalence trials, it is necessary to use statistical analysis in conjunction with clinical judgment when conducting a noninferiority trial. The choice of the noninferiority margin, which must be made before the trial is conducted, is a clinical judgment. Once the data have been collected, a statistical technique is used to determine whether the new drug is deemed to be noninferior compared with the reference drug. 

Committee for Medicinal Prodncts for Hnman Use (2005) Guideline on the choice of the noninferiority margin. London, European Medicine Agency. 

Although conventional p-values have no role to play in equivalence or noninferiority trials there is a p-value counterpart to the confidence intervals approach. The confidence interval methodology was developed by Westlake (1981) in the context of bioequivalence and Schuirmann (1987) developed a p-value approach that was mathematically connected to these confidence intervals, although much more difficult to understand It nonetheless provides a useful way of thinking, particularly when we come later to consider type I and type II errors in this context and also the sample size calculation. We will start by looking at equivalence and use A to denote the equivalence margins. 

Consider two examples from previous chapters that illustrate this. In Chapter 9, discussions of sample-size estimation emphasized that the process is indeed one of estimation rather than pure calculation. A calculation is certainly executed, but the values that are placed into the appropriate formula are chosen by the sponsor. On each occasion, the sponsor must consider the influences of the choices that are made and make the most appropriate decision in the specific context of that trial. In Chapter 11, equivalence and noninferiority designs were discussed. In addition to the calculations that are involved using the data collected in a trial, equivalence or noninferiority margins must be established before the trial commences. Their choice is a clinical choice, not a statistical choice, and subjectivity is necessarily involved in this choice. Thus, the discipline of Statistics certainly involves using informed judgments. Statistics really is an art as well as a science, a sentiment well expressed by Katz (2001) as cited in Chapter 13. 

In a sense, virtually, all clinical trials can be considered to be safety noninferiority trials, since virtually, all trials collect safety information and therefore provide evidence as to whether or not there is an important difference in safety between treatments. However, there are two key distinguishing characteristics of the trials that we refer to as safety non-inferiority trials in this chapter a safety endpoint is designated as primary and a noninferiority margin is prespecified. In the next section, we will discuss some of the issues associated with non-inferiority trials in general, focusing on the factors that are unique to safety non-inferiority trials. 

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