⬆️S͙U͙P͙E͙R͙I͙O͙R͙I͙T͙Y͙ T͙R͙I͙A͙L͙S͙
✔️Seek to establish that one treatment is better than another
✔️The sample size is set so that there is high statistical power to detect a clinically meaningful difference between the two treatments
↔️E͙Q͙U͙I͙V͙A͙L͙E͙N͙C͙E͙ T͙R͙I͙A͙L͙S͙
✔️Seek to test if a new treatment is similar in effectiveness to an existing one
✔️Appropriate if the new treatment has certain benefits such as fewer side effects, being easier to use, or being cheaper
✔️Designed to be able to demonstrate that, within given acceptable limits, the two treatments are equally effective
✔️Equivalence is a pre-set maximum difference between treatments such that, if the observed difference is less than this, the two treatments are regarded as equivalent . The tighter the limits of equivalence are set, the larger the sample size that will be required
✔️A serious condition requires tighter limits for equivalence than a less serious condition.
✔️The calculated sample size tends to be bigger for equivalence trials than superiority trials
๐ดT͙H͙I͙N͙G͙S͙ T͙O͙ R͙E͙M͙E͙M͙B͙E͙R͙
๐๐ฟIn general the design and implementation of equivalence trials is less straight forward than superiority trials
๐๐ฟIf patients are lost to follow-up or fail to comply with the trial protocol, then any differences between the treatments is likely to be reduced and so equivalence may be incorrectly inferred.
๐๐ฟSo equivalence trials need very strict management and good patient follow-up to minimize these problems
๐๐ฟIt is often helpful to include a secondary analysis where subjects are analysed according to the treatment they actually received, ‘per protocol’ analysis
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Reference: Oxford Handbook of Medical Statistics, Janet L. Peacock , Philip J. Peacock
