Efficacy equivalence or noninferiority

The conventional clinical trial compares a standard treatment with a new treatment which, it is hoped, may improve outcome; this we refer to as an 'efficacy' trial. In some situations, a new treatment maybe expected to have a similar, rather than better, effect on outcome to the standard treatment, but perhaps to have other advantages; for example, a better toxicity profile, a more convenient means of administration or a lower cost. A trial comparing these treatments would aim to show that the difference in impact on the primary outcome measure lies within a pre-specified acceptable range, and would present data on the other outcome measures that would, it is hoped, demonstrate the advantages that the new treatment brings. This is an 'equivalence trial,' so called because one is attempting to demonstrate the clinical equivalence of two treatments. This is different from absolute equivalence - that is, an identical outcome in the two groups -which can never be demonstrated in a clinical trial with a finite number ofpatients. The term 'clinical equivalence' implies that, on balance, the costs and benefits associated with the treatment options are such that both treatments provide acceptable alternatives.

A 'non-inferiority trial' is a specific type of equivalence trial in which one compares a standard treatment to a new treatment, which is not necessarily expected to be better than standard with respect to the most important outcome measure, but perhaps as good or slightly worse, within a carefully specified range. Again, the new treatment is expected to bring other benefits, and the new treatment would be defined as equivalent (or noninferior) if any disadvantage with respect to the major outcome measure is sufficiently outweighed by the benefits it brings. In cancer therapy trials, this often brings about a situation in which a trade-off is made between possible gains for all patients allocated a particular treatment (e.g. reduced toxicity) and possible losses for some patients, for example a higher recurrence rate. This is clearly a very difficult balance to strike, and one which patients, doctors, and those designing trials may see very differently. In Chapter 5, we discuss some ways in which the information necessary to design such trials might be elicited. It is important to note that a non-inferiority trial should only be considered if there is sufficiently strong evidence that standard therapy is better than no treatment. Where this is not the case, demonstrating non-inferiority of a new therapy over standard therapy will not necessarily have proved that it is better than no treatment.

Both equivalence and non-inferiority trials have perhaps their greatest role where cure rates are high, but there is a wish to reduce as far as possible the morbidity of treatment without compromizing efficacy (for example, stage I testicular seminoma) or where survival rates are very low, and the aim is to provide the best palliation while again avoiding adverse effects on already low survival rates (for example, poor prognosis small cell lung cancer patients).

It is important to make the distinction between efficacy, equivalence and non-inferiority when developing a trial since it should affect the design, not least the trial size. If the aim is really to show that two treatments are equivalent, then the size of difference the trial must be powered to detect (or exclude) logically must be less than the size of difference that would be considered sufficient to prove the efficacy of one of the treatments (it is predominantly this fact, more than technical differences in the way sample sizes are calculated, that makes 'equivalence' trials generally much larger than efficacy trials).

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