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.
Original language | English (US) |
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Pages (from-to) | 1042-1053 |
Number of pages | 12 |
Journal | Journal of Biopharmaceutical Statistics |
Volume | 23 |
Issue number | 5 |
DOIs | |
State | Published - Sep 3 2013 |
Bibliographical note
Funding Information:We thank the referee, an associate editor, and the editor for their comments and suggestions on an earlier version of the article, which were incorporated in the article and substantially improved it. This research was supported by the Review Science Research Funds number RSR-10-19, granted by the Center for Drug Evaluation and Research of the U.S. Food and Drug Administration. This article reflects the views of the authors and should not be construed to represent the U.S. FDA’s views or policies.
Keywords
- Constancy assumption
- Covariate-adjustment approach
- Fixed margin approach
- Generalizedlinear model
- Noninferiority margin