A Note on Partial Covariate-Adjustment and Design Considerations in Noninferiority Trials When Patient-Level Data are not Available

被引:0
作者
Nie, Lei [1 ,4 ]
Soon, Guoxing [1 ]
Qi, Karen [1 ]
Chen, Yong [2 ]
Chu, Haitao [3 ]
机构
[1] US FDA, Div Biometr 4, Off Biometr CDER OTS FDA, Silver Spring, MD 20993 USA
[2] Univ Texas Hlth Sci Ctr Houston, Div Biostat, Houston, TX 77030 USA
[3] Univ Minnesota, Sch Publ Hlth, Dept Biostat, Minneapolis, MN USA
[4] Univ Maryland, Dept Epidemiol & Prevent Med, Baltimore, MD 21201 USA
关键词
Constancy assumption; Covariate-adjustment approach; Fixed margin approach; Generalized linear model; Noninferiority margin; RESISTANT HIV-1 INFECTION; GENOTYPE; INFECTION; ISSUES; RALTEGRAVIR; BOCEPREVIR; CHOICE; DELTA;
D O I
10.1080/10543406.2013.813523
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
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.
引用
收藏
页码:1042 / 1053
页数:12
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