Design Considerations and Dealing with Non-continuous Endpoints
In this webinar, we explore how to determine the appropriate sample size for non-inferiority studies. Non-inferiority means testing if a proposed treatment is no worse than an existing approach by showing it is above the non-inferiority bound. We review the important design considerations for non-inferiority testing including how to select the non-inferiority bound and demonstrate how to determine the sample size for continuous, binomial, survival and count data. Further below, you will find the webinar recording, slides and worked examples.
More About The Webinar
Non-inferiority testing is used to test if a new treatment is not inferior to a standard treatment. This is a common objective in the areas such as medical devices and generic drug development. For example, if a proposed device or treatment were less invasive than the standard treatment then non-inferiority would be an appropriate route to improve patients’ treatment choices.
To test for non-inferiority, the treatment group is tested to verify it is above the non-inferiority margin. The non-inferiority margin is a level below equality that would still be considered acceptably non-inferior to the standard treatment. The definition of the non-inferiority margin is a matter of significant debate and is an important aspect of regulatory guidance from agencies such as the FDA.
Non-inferiority studies can be conducted for a wide variety of different endpoints including continuous, binomial, survival and count endpoints. Each of these endpoints present unique design and statistical considerations with a wide range of potential design choices. For example, common designs for non-inferiority are crossover designs, three arm trials and parallel arm trials.
In this webinar, we review non-inferiority testing design considerations and demonstrate how to determine the sample size for a wide variety of endpoints and designs.
