A non-inferiority trial

A well-executed clinical trial that correctly demonstrates the treatments to be similar can not be distinguished, on the basis of the data alone, from a poorly executed trial that fails to find a true difference.

Therefore, a noninferiority trial must rely on an assumption of assay sensitivity on the basis of information external to the trial, such as the quality control procedures or the reputation of the investigator.

The International Conference on Harmonization guidelines [ 9 ] list a number of factors that can reduce assay sensitivity. These include poor compliance with the study medication, poor diagnostic criteria, excessive variability of measurements, and biased end-point assessment. In order to be credible, therefore, noninferiority trials must attempt to avoid these factors to every possible extent, and even then might not be able to escape suspicion.

For example, a successful superiority trial can be very credible despite a moderately large rate of discontinuation from study drug, but a successful noninferiority trial would be less so, because discontinuations can obscure a true treatment effect and thus reduce assay sensitivity.

Intention-to-treat ITT is widely recognized as the most valid analytic approach for superiority trials that involve long-term end-point follow up, because it adheres to the randomization procedure and is generally conservative [ 10 ].

Although some might argue that the ITT analysis is overly conservative, most would agree that a positive ITT analysis of a superiority trial is convincing. Unfortunately, no such conservative analysis exists for noninferiority trials. For example, including data after study drug discontinuation in the analysis, as ITT does, tends to bias the results toward equivalence, which could make a truly inferior treatment appear to be noninferior.

The per-protocol analysis, on the other hand, excludes data from patients with major protocol violations. However, excluding these data can substantially bias the results in either direction.

For example, patients in a survival trial might discontinue study medication due to the development of heart failure, which is a strong risk factor for mortality.

Therefore, noninferiority trials are often analyzed using ITT and per-protocol approaches, and only if both approaches support noninferiority is the trial considered positive.

Even in this case, however, the possibility of bias can not be ruled out, and it can be awkward to have different analytic strategies for superiority and noninferiority trials. Blinding is one of the most important bias-avoiding techniques available to clinical trialists.

It is not always feasible to blind the investigator or patient to the treatment regimen, but blinded end-point determination is nearly always possible and should be done, particularly when the end-point has a subjective component. However, blinding does not protect against bias nearly as well in a noninferiority trial as it does in a superiority trial. In a superiority trial, a blinded investigator can not consciously or subconsciously influence the results to support a preconceived belief in superiority, but in a noninferiority trial there is no protection against a blinded investigator biasing the results toward a preconceived belief in equivalence by assigning similar ratings to the treatment responses of all patients.

It can be quite difficult to specify an appropriate noninferiority margin. There are two basic approaches, both of which have serious drawbacks.

One approach is to specify the equivalence margin on the basis of a clinical notion of a minimally important effect. However, this is clearly subjective, and it is possible with this approach to set the equivalence margin to be greater than the effect of the active control, which could lead to harmful treatments fitting within the definition of noninferiority.

To avoid this, the equivalence margin is often chosen with reference to the effect of the active control in historical placebo-controlled trials. When the equivalence margin is chosen in this way, there is some basis on which to claim that a positive noninferiority trial implies that the new treatment is superior to placebo.

However, this claim requires an assumption that the effect of the active control in the current trial is similar to its effect in the historical trials. That assumption can be undermined by differences with respect to design features eg the patient population, dosage regimen of the active control, end-point definition or concomitant therapies , or by an inconsistency in the effect of the active controls among the historical placebo-controlled trials beyond that expected by random chance.

For this reason, the equivalence margin usually includes some type of buffer. Although noninferiority trials typically have smaller sample sizes than active-controlled superiority trials, they can have considerably larger sample sizes than placebo-controlled trials.

This is because the equivalence margin is often much smaller than the treatment difference for which a placebo-controlled trial is powered. Any apparent positive trial based on this margin, showing a treatment in noninferior to current treatment may be no better than placebo. Is the maximum extent of clinical noninferiority included in the noninferior margin acceptable for you? For your patient? Does the method of data analysis bias the results toward the null value, thus making it more likely to generate a conclusion of noninferiority?

Intention to treat analysis may bias result toward the null value thus providing a conservative estimate for effect size in superiority trials but has the opposite effect in noninferiority trials.

At the same time, how the authors handled loss to follow-up should be reviewed since when you have loss to follow up or cross over between groups the trial becomes more likely to conclude NI, in contrast to a superiority trial where such biases will make the trial less likely to conclude superiority.

Does the design of the trial enhance the risk of type I errors? In other words, a poorly designed non-inferiority trial can lead to the adoption of a useless treatment. Mauri, L. Challenges in the Design and Interpretation of Noninferiority Trials. New England Journal of Medicine, 14 , — Understanding noninferiority trials.

Korean journal of pediatrics, 55 11 , — As the name suggests, the aim is to show that the new treatment is not inferior to the existing one — that is, it is either equally effective or better.

If this can be established, the new treatment can be considered as a replacement for the existing treatment, especially if it has other advantages e. We will explain what this is in the following example. If the two treatments were compared in a study with a small sample size, the results might be something like those shown in the figure below:. Would this establish that the new treatment is not inferior to the existing one? No — based on these results, the new treatment might reduce survival time by as much as 5 months compared to the existing treatment, which is clearly much worse.

Even though we may assume that this difference is small enough to conclude non-inferiority, this is where the non-inferiority margin comes in. In the current example, a difference of one month, say, might be the maximum that can be considered equal, so the non-inferiority margin would be one month.

The aim of the study would then be to exclude the possibility that the difference was more than one month. Once the non-inferiority margin has been set, the CI for the difference is compared to the margin to decide the outcome of the trial.

If the CI is entirely above the margin, the new treatment is non-inferior to the existing one. Clearly the outcome of a non-inferiority trial depends critically on the non-inferiority margin.

In the example above, if the non-inferiority margin had been, say, 2 months, non-inferiority would also have been demonstrated in scenario D. Given this importance, it is important to set the non-inferiority margin in advance and to do so in an objective way. Indeed, the ICH guidance ref 1 requires that the non-inferiority margin is specified in the clinical trial protocol. If you want to ensure you receive this as soon as we publish it and you are not already a subscriber to Quantics Biostatistics Blog please sign up below.

Statistical Principles for Clinical Trials E9. September