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Non-inferiority trials are commonly seen in medical device trials. However, the violation of the constancy assumption could be a serious concern. Some approaches have been proposed to address the impact of violation of the constancy assumption on the validity of a non-inferiority trial such as prevention through good trial conduct and adjustment through analysis. In this paper, we propose a new approach via adding a companion constancy test to the non-inferiority test that consequently protects the validity of a non-inferiority trial under Bayesian framework. In addition, as some clinical data from historical studies are available for the active control prior to the start of the investigational study, we consider two different methods to borrow the available information. We use a simulation study to assess the performance of the proposed approach.

Current statistical design and analysis of multiregional clinical trials for medical devices generally follows a paradigm where the treatment effect of interest is assumed consistent among US and OUS regions. In this paper, we discuss the situations where the treatment effect might vary among US and OUS regions, and propose a two-component Bayesian approach for targeted decision making. In this approach, anticipated treatment difference among US and OUS regions is formally taken into account by design, hopefully leading to increased transparency and predictability of targeted decision making.

The number of clinical trials conducted simultaneously in the USA and outside of the US (OUS) for medical device development has been increasing over the last decade. However, the presence of inherent regional differences in treatment effects poses a great challenge to the US regulatory agency’s decision making. In this chapter, we propose a two-tier procedure for analyzing data from such trials for the US regulatory agency’s decision making, allowing treatment effects to vary from region to region. We differentiate direct evidence from supporting evidence while using both to exemplify the advantage of such trials for the US regulatory agency’s decision making. The contribution of the supporting evidence can be adjusted according to the expectation of the magnitude of regional differences and the statutory requirements in the USA. Examples are presented to illustrate the design and analysis based on our proposed procedure. Using the proposed two-tier procedure with an upfront explicit decision tree can increase the predictability and transparency of the regulatory decision making.