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A note on partial covariate-adjustment and design considerations in noninferiority trials when patient-level data are
Lei Nie1, Guoxing Greg Soon, Karen Qi
1U.S. Food and Drug Administration (US FDA), Division of Biometrics IV, Office of Biometrics/CDER/OTS/FDA, Silver Spring, Maryland 20993, USA. lei.nie@fda.hhs.gov
Abstract:
The traditional fixed margin approach to evaluating an experimental treatment through an active-controlled noninferiority trial is simple and straightforward. However, its utility relies heavily on the constancy assumption of the experimental data. The recently developed covariate-adjustment method permits more flexibility and improved discriminatory capacity compared to the fixed margin approach. However, one major limitation of this covariate-adjustment methodology is its adherence on the patient-level data, which may not be accessible to investigators in practice. In this article, under some assumptions, we examine the feasibility of a partial covariate-adjustment approach based on data typically available from journal publications or other public data when the patient-level data are unavailable. We illustrate the usefulness of this approach through two real examples. We also provide design considerations on the efficiency of the partial covariate-adjustment approach.
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