Adjusting for Unknown Bias in Noninferiority Clinical Trials
被引:9
作者:
Odem-Davis, Katherine
论文数: 0引用数: 0
h-index: 0
机构:
Univ Washington, Ctr Biomed Stat, Seattle, WA 98195 USAUniv Washington, Ctr Biomed Stat, Seattle, WA 98195 USA
Odem-Davis, Katherine
[1
]
Fleming, Thomas R.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Washington, Dept Biostat, Seattle, WA 98195 USA
Fred Hutchinson Canc Res Ctr, Seattle, WA 98109 USAUniv Washington, Ctr Biomed Stat, Seattle, WA 98195 USA
Fleming, Thomas R.
[2
,3
]
机构:
[1] Univ Washington, Ctr Biomed Stat, Seattle, WA 98195 USA
[2] Univ Washington, Dept Biostat, Seattle, WA 98195 USA
[3] Fred Hutchinson Canc Res Ctr, Seattle, WA 98109 USA
来源:
STATISTICS IN BIOPHARMACEUTICAL RESEARCH
|
2013年
/
5卷
/
03期
关键词:
Active control;
Constancy;
Delta;
Equivalence;
Margin;
NON-INFERIORITY TRIALS;
DESIGN;
D O I:
10.1080/19466315.2013.795910
中图分类号:
Q [生物科学];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Evaluation of noninferiority is based on ruling out a threshold for what would constitute unacceptable loss of efficacy of an experimental treatment relative to an active comparator "Standard." This threshold, the "noninferiority margin," is often based on preservation of a percentage of Standard's effect. To obtain an estimate of this effect to be used in the development of the "noninferiority margin," data are needed from earlier trials comparing Standard to Placebo if the noninferiority trial does not have a Placebo arm. This approach often provides a biased overestimate of Standard's true effect in the setting of the current noninferiority study. We describe two commonly used noninferiority margin methods that adjust for this bias, the two-confidence interval (95-95), and the Synthesis margins. However, the added " variance inflation" adjustment made by 95-95 margin diminishes with increasing information from historical trial(s), and the Synthesis margin is based on a strong assumption that the relative bias is known. We introduce an alternative "Bias-adjusted" margin addressing vulnerabilities of each by attenuating the estimate and by accounting for uncertainty in the true level of bias. Examples and asymptotic estimates of noninferiority hypothesis rejection rates in the proportional hazards setting are used to compare methods.