Show Summary Details
Page of

Equivalence and Noninferiority Trials 

Equivalence and Noninferiority Trials
Study Design and Statistics

Margaret A. Winker

and Stephen J. Lurie

Page of

PRINTED FROM AMA MANUAL OF STYLE ONLINE ( © American Medical Association, 2009. All Rights Reserved. Under the terms of the license agreement, an individual user may print out a PDF of a single chapter of a title in AMA Manual of Style Online for personal use (for details see Privacy Policy and Legal Notice).

Subscriber: null; date: 20 June 2018

Equivalence and Noninferiority Trials

It is sometimes desirable to compare a less expensive treatment or intervention against a treatment or intervention that is already known to be effective. In these cases, it would be unethical to expose participants to an inactive placebo. Thus, these trial designs assess whether the treatment or intervention under study (the “new intervention”) is no worse than an existing alternative (the “active control”).

In equivalence and noninferiority trials, authors must prespecify a margin of noninferiority (Δ), within which the new intervention can be assumed to be no worse than the active control. There are a number of methods for arriving at the value Δ. Because different methods of estimating Δ may be more defensible in some situations than others, authors should provide clear explanations of their method and rationale for arriving at their value for Δ. Noninferiority trials test the 1-sided hypothesis that the effect of the new intervention is no more than Δ units less than the active control. Equivalence trials, which are less common than noninferiority trials, test the 2-sided hypothesis that the effect of the new treatment lies within the range of Δ to −Δ.

Although use of intention-to-treat (ITT) analysis is optimal in trials that test whether one treatment is superior to another, use of such analysis can bias the results of equivalence and noninferiority trials. Thus, in addition to ITT analysis, authors should report results for only participants who completed the trial.

Interpretation of the results depends on the confidence interval for the difference between the new intervention and the active placebo, and whether this confidence interval crosses Δ, −Δ, and 0. See Table 2.

Table 2. Checklist of Items for Reporting Noninferiority or Equivalence Trials (Additions or Modifications to the CONSORT Checklist Are Indicated in Footnotes)a

Paper Section and Topic

Item No.

Noninferiority or Equivalence Trials

Title and abstract


How participants were allocated to interventions (eg, “random allocation,” “randomized,” or “randomly assigned”), specifying that the trial is a noninferiority or equivalence trial.




Scientific background and explanation of rationale, including the rationale for using a noninferiority or equivalence design.




Eligibility criteria for participants (details whether participants in the noninferiority or equivalence trial are similar to those in any trial(s) that established efficacy of the reference treatment) and the settings and locations where the data were collected.



Precise details of the intervention intended for each group, detailing whether the reference treatment in the noninferiority or equivalence trial are identical (or very similar) to that in any trial(s) that established efficacy, and how and when they were actually administered.



Specific objective and hypotheses, including the hypothesis concerning noninferiority or equivalence.



Clearly defined primary and secondary outcome measures, detailing whether the outcomes in the noninferiority or equivalence trial are identical (or very similar) to those in any trial(s) that established efficacy of the reference treatment and, when applicable, any methods used to enhance the quality of measurements (eg, multiple observations, training of assessors).

    Sample size


How sample size was determined, detailing whether it was calculated using a noninferiority or equivalence criterion and specifying the margin of equivalence with the rationale for its choice. When applicable, explanation of any interim analysis and stopping rules (and whether related to a noninferiority or equivalence hypothesis).


    Sequence generation


Method used to generate the random allocation sequence, including details of any restriction (eg, blocking, stratification).

    Allocation concealment


Method used to implement the random allocation sequence (eg, numbered containers or central telephone), clarifying whether the sequence was concealed until interventions were assigned.



Who generated the allocation sequence, who enrolled participants, and who assigned participants to their groups.

    Blinding (masking)


Whether or not participants, those administering the interventions, and those assessing the outcomes were blinded to group assignment. When relevant, how the success of blinding was evaluated.

    Statistical methods


Statistical methods used to compare groups for primary outcome(s), specifying whether a 1- or 2-sided confidence interval approach was used. Methods for additional analyses, such as subgroup analyses and adjusted analyses.


    Participant flow


Flow of participants through each stage (a diagram is strongly recommended). Specifically, for each group report the numbers of participants randomly assigned, receiving intended treatment, completing the trial protocol, and analyzed for the primary outcome. Describe protocol deviations from trial as planned, together with reasons.



Dates defining the periods of recruitment and follow-up.

    Baseline data


Baseline demographic and clinical characteristics of each group.

    Numbers analyzed


Number of participants (denominator) in each group included in each analysis and whether “intention-to-treat” and/or alternative analyses were conducted. State the results in absolute numbers when feasible (eg, 10 of 20, not 50%).

    Outcomes and estimation


For each primary and secondary outcome, a summary of results for each group and the estimated effect size and its precision (eg, 95% confidence interval). For the outcome(s) for which noninferiority or equivalence is hypothesized, a figure showing confidence intervals and margins of equivalence may be useful.

    Ancillary analyses


Address multiplicity by reporting any other analyses performed, including subgroup analyses and adjusted analyses, indicating those prespecified and those exploratory.

Adverse events


All important adverse events or side effects in each intervention group.




Interpretation of the results, taking into account the noninferiority or equivalence hypothesis and any other trial hypotheses, sources of potential bias or imprecision, and the dangers associated with multiplicity of analyses and outcomes.



Generalizability (external validity) of the trial findings.

    Overall evidence


General interpretation of the results in the context of current evidence.

a From Piaggio et al.10

b Expansion of corresponding item on CONSORT checklist.4,11

Authors should refer to specific CONSORT guidelines for reporting the design and results of equivalence and noninferiority trials.10

Previous | Next