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Non-Inferiority Trial

Non-Inferiority Trial

 YUKON Choice PC is one of few drug eluting stents which have undergone robust equivalence and non –inferiority trials with the existing DES technologies. In a unique trial ISAR TEST 4 which was published in Journal Of American college of Cardiology, YUKON choice PC was compared with Xience and Cypher with 2: 1 randomisation in over 2600 patients.YUKON PC showed non inferiority to Xience and Cypher despite using minimal polymer.

There is increasing interest in determining whether a new treatment — pharmacological or non-pharmacological — is similar to (equivalent) or no worse than (non-inferior) the standard in terms of efficacy, but preferable owing to lower cost, fewer side effects, easier administration or less harm .Equivalence and non-inferiority trials assess whether the effects of a new treatment, compared with a standard treatment as the active control, stay within or go beyond a predefined clinically acceptable margin — the equivalence or non-inferiority margin. These study designs are useful in situations where a placebo or no-treatment group is considered unethical, such as treating patients with myocardial infarction. Another driver is the mandatory requirement of regulatory and licensing agencies for comparisons of new treatments with existing treatments.

In the absence of a placebo control, equivalence and non-inferiority trials rely on certain assumptions:

  • Superior efficacy of the standard treatment over placebo has been convincingly proven for a given indication in previous trials.
  • Efficacy of the standard treatment will be preserved under the conditions of the equivalence or non-inferiority trial.
  • If the new treatment is shown to have equivalent or non-inferior efficacy, then it too would exhibit superior efficacy to placebo if a placebo-controlled trial were to be performed.

These assumptions, and the rationale for equivalence or non-inferiority margins, cannot be validated explicitly. Although new and standard treatments may be shown to be equivalent, they could both be ineffective.

 


 

General Principles

In superiority trials, a minimum clinically important difference between two treatments is hypothesised and, because the new treatment could be either better or worse than the standard treatment, two-sided statistical tests are used to test the null hypothesis (H0) of no difference between treatments). This difference is usually measured in absolute units (eg, 2 percentage points for a mortality rate or 5 points on a symptom scale), but can be expressed in relative terms (relative risk or odds ratio). The sample size needed to show a difference, if one exists, is calculated from the hypothesised minimum difference, estimates of event rates in the standard treatment group, numbers of participants who might drop out or cross over between treatments, and the chosen level of statistical significance (usually 5%).

In an equivalence trial, a bidirectional equivalence interval is specified and a two-sided test is used to test the null hypothesis that the new treatment is either better or worse than the standard, as revealed by effect estimates lying outside the symmetrical equivalence margins (− Δ to + Δ). In a non-inferiority trial, the prime interest is determining whether the new treatment is no worse than the non-inferiority margin (+ Δ) which, if exceeded, defines the new treatment as being unequivocally inferior. As the difference of interest is in one direction only, one-sided statistical tests can be used to test the null hypothesis that the new treatment is worse than the standard, and, if the statistical chance of this being seen is less than 5%, the alternative hypothesis (Ha) of non-inferiority is accepted.

As no trial is infinitely large, any observed difference between new and standard treatments is an imprecise estimate of the difference. The level of imprecision is denoted by the width of the confidence interval (CI). If the null hypotheses are to be rejected, the upper limit of the CI around the observed difference (ie, the most unfavourable result for the new treatment that is possible given the level of imprecision) should lie within the equivalence margin for equivalence trials, and be less than the non-inferiority margin in non-inferiority trials. The sample size required to avoid rejecting a truly equivalent or non-inferior treatment is again based on the chosen value of the margin in addition to other factors already mentioned for superiority trials.


 

 Design

The study protocol should specify that testing for non-inferiority between two active treatments is one objective — or the only objective — and justify the absence of an inactive control group. Measures of the primary (efficacy) outcome (eg, rates of death or specific clinical events) and of secondary outcomes (eg, costs, side effects, patient adherence, safety) should be clearly defined. In some situations, such as the case study in greater safety (eg, fewer major bleeds) at the cost of similar or lower efficacy (eg, fewer strokes) can be assessed as a combined endpoint that measures an adjusted or weighted algebraic trade-off of the two items. The extent to which outcome measures and their methods of ascertainment are similar to those used in the original placebo-controlled trials of standard treatment should also be stated.

Non-inferiority margin. Sound clinical judgement and statistical reasoning are required in defining the non-inferiority margin.

Clinical judgement: the non-inferiority margin should be the smallest clinically meaningful difference between treatments after considering the seriousness of the primary and secondary outcomes. Margins for mortality or disabling events should be more stringent than those for symptom control or quality of life. For serious efficacy endpoints, many experts stipulate that the margin should be no more than 50%, and preferably no more than 20%, of the treatment effect of the standard treatment, as established in placebo-controlled superiority trials. However, no validated rule for calculating the margin currently exists, and many trials use margins that statisticians regard as too liberal.Wherever possible, the margin should be validated by published expert consensus,and not left to the sole discretion of the investigators and sponsors.

Statistical reasoning: as the magnitude of the standard treatment effect directly influences calculation of the non-inferiority margin, it should be calculated as precisely as possible. Reference should be made to a meta-analysis of all placebo-controlled trials of the standard treatment, in which a summary estimate of effect and its 95% CI are calculated using a random-effects model that demarcates the widest boundaries of uncertainty around the point estimate of effect .When individual trials have heterogeneous results, the summary estimate should be expressed in both absolute and relative terms. The non-inferiority margin should preferably be no greater than half of the lower limit of the 95% CI of the standard treatment effect.Extrapolating this treatment effect from historical superiority trials to a non-inferiority trial involves two assumptions. First, the characteristics of the historical trials closely resemble those of the non-inferiority trial — this is termed “constancy”. Second, both trials are capable of distinguishing between effective and ineffective treatments — “assay sensitivity”. As previously discussed, these assumptions cannot be verified in the absence of a placebo control group.

Sample size : The method for calculating sample size needs to be clearly articulated in the study protocol. Non-inferiority trials usually require larger sample sizes than superiority trials because the non-inferiority margin is smaller than the treatment effects assessed by superiority trials and study power needs to be higher (usually 90%) for a non-inferiority trial, to minimise the risk that a non-inferior treatment is missed due to chance.

Blinding :In contrast to unequivocal endpoints such as death, endpoints requiring subjective interpretation are more vulnerable to bias. In a superiority trial, this bias can be minimised by randomising and concealing allocation and blinding outcome assessors, which makes it impossible to know which participants will be, or were, allocated to a particular treatment. However, no such protection exists in a non-inferiority trial. Even with blinding, investigators could potentially randomly discount a significant proportion of endpoints as not meeting pre-specified event definitions, knowing that this will bias the results towards showing non-inferiority. Unblinded trials with highly subjective endpoints are especially susceptible .Consequently, quality-control procedures and endpoint assessment must be rigorous and at “arms length” from investigators and sponsors.

Study Conduct

Fidelity with historical placebo-controlled trials of standard treatment : To ensure no unfair advantage is accorded to the new treatment over the standard, study conduct must closely resemble that of historical trials that compared standard treatment with placebo. Similarities should include patient characteristics, use of the standard treatment (dose, frequency, duration and method of administration), co-interventions, and outcome measures.

Enhancing assay sensitivity : To better distinguish between inferior and non-inferior treatments, investigators should make deliberate efforts to maximise recruitment of patients who are likely to respond to both new and standard treatments in terms of the primary efficacy endpoint and likely to comply with the study protocol. Efforts should also be made to minimise use of non-protocol co-interventions, patient “drop out”, and misclassification of outcomes. Some reassurance about assay sensitivity is provided by seeing standard treatment effects of similar magnitude to those in historical trials. Nevertheless, a well executed non-inferiority trial that correctly demonstrates non-inferiority cannot be distinguished, on the basis of outcome data alone, from a poorly executed trial that does not find a true difference.

Analysis and reporting of results

Intention-to-treat versus per-protocol analysis: In superiority trials, intention-to-treat (ITT) analysis of outcomes at study end (ie, according to the treatment group to which participants were originally assigned and irrespective of adherence to study protocol) is preferred to per-protocol (PP) analysis (ie, using outcomes from only those participants who fully complied with the study protocol). This is because ITT analyses yield the most conservative estimate of treatment effect that can be expected in real-world settings, given the inevitability of some patients withdrawing from one or other treatment group because of side effects, crossover to alternative treatment, or refusal to continue. In a non-inferiority trial, ITT analysis is thus more likely to narrow the difference between treatments and yield a non-inferior result. Consequently, a PP analysis is needed to cross-validate the ITT analysis, while bearing in mind substantial variation between treatment groups in rates and reasons for drop-out may also invalidate PP analyses.

Statistical analysis : A non-inferiority trial should specify whether a one- or two-sided CI is placed around the estimate of difference between treatments. If a two-sided test is used, the 95% CI applies; if a one-sided test is used, the 97.5% CI applies. Use of more liberal 90% CIs should be viewed with caution. Ideally, a figure that depicts the CI and non-inferiority margin (or equivalence limits) should be included.

Sensitivity analyses: To assess the robustness of a non-inferiority trial result, data should, where appropriate, be analysed according to absolute versus relative risks, ITT versus PP analyses, and one-sided versus two-sided CIs.

Post-hoc analyses : Both non-inferiority and superiority can be assessed in the same trial without statistical penalty provided the testing of both hypotheses has been pre-specified and the sample size calculated on the basis of the chosen non-inferiority margin, which should be smaller than the superiority margin. Trials that are designed to test a superiority hypothesis but generate non-significant results cannot be re-analysed post-hoc to test for equivalence or non-inferiority.

Interpretation of results : Conclusions should be consistent with study results and expressed with the vocabulary used to define the original trial aims. Ideally, the title of the study report should indicate that a non-inferiority study design was used. Sources of potential bias or imprecision should be discussed, especially those involving secondary outcomes that favour the new treatment.


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