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ABSTRACT
To speed up the process of bringing a new drug to the market, more and more clinical trials are being conducted simultaneously in multiple regions. After demonstrating the overall drug’s efficacy across regions, the regulatory and drug sponsor may also want to assess the drug’s effect in specific region(s). Most of the recent approaches imposed a uniform criterion to assess the consistency of treatment effects between the interested region(s) and the entire study population regardless of the number of regions in multiregional clinical trials (MRCT). As a result, the needed sample size to achieve the desired probability of satisfying the regional requirement could be huge and implausible for the trial sponsors to implement.
In this paper, we propose a unified additional requirement for regional approval by differing the parameters in the additional requirement depending on the number of planned regions. In particular, the values of the parameters are determined by a reasonable sample size increase with the desired probability satisfying the additional requirement. Considering the practicality of the global trial or sample size increase, we recommend specific values of the parameters for a different number of planned regions. We also introduce the assurance probability curve to evaluate the performance of different regional requirements.
Acknowledgments
The authors thank the editor and anonymous reviewers of the Journal of Biopharmaceutical Statistics for their suggestions. This research was done as part of US Food and Drug Administration ORISE internship when Dr. Zhaoyang Teng, the first author, was a graduate student studied at Boston University.
Appendix
The formula for the assurance probability of region i by imposing the unified additional requirement can be derived as follows:
where is the test statistic of the following hypothesis test at the one-sided
significance level:
Denote the treatment difference of region i,
the treatment difference of all regions combined other than
Assume:
Then:
Thus:
where and
are the probability measures with respect to
and
, respectively, and:
Consider the special case 1: as the regional requirement, and assume that the mean and variance of the treatment effects are uniform across regions, the total samples are evenly distributed to each region; namely
. If we increase the total sample size to
of the sample size calculated by the traditional method:
, then:
where is the type II error rate under these assumptions.
Thus, the parameters in the formula of
under these assumptions are reduced as follows:
When the true treatment effect in region i is smaller than the other regions, that is, , where
,
is the true treatment effect for other regions, the assurance probability under this setting becomes the following:
If we increase the total sample size toof the sample size calculated by the traditional method:
, and the total samples are evenly distributed to each region, namely
. Then:
where is the type II error rate under these assumptions.
Thus, the parameters in the formula of
under these assumptions are reduced as follows: