Noninferiority testing beyond simple two-sample comparison.
In order to fulfill the requirement of a new drug application, a sponsor often need to conduct multiple clinical trials. Often these trials are of designs more complicated than a randomized two-sample single-factor study. For example, these trials could be designed with multiple centers, multiple factors, covariates, group sequential and/or adaptive scheme, etc. When an active standard treatment used as the control treatment in a two-arm clinical trial, the efficacy of the test treatment is often established by performing a noninferiority test through comparison of the test treatment and the active standard treatment. Typically, the noninferiority trials are designed with either a generalized historical control approach (i.e., noninferiority margin approach or delta-margin approach) or a cross-trial comparison approach (i.e., synthesis approach or lambda-margin approach). Many of the statistical properties of the approaches discussed in the literature were focused on testing in a simple two sample comparison form. We studied the limitations of the two approaches for the consideration of switching between superiority and noninferiority testing, feasibility to be applied with group sequential design, constancy assumption requirements, test dependency in multiple trials, analysis of homogeneity of efficacy among centers in a multi-center trial, data transformation and changing analysis method from the historical studies. Our evaluation shows that the cross-trial comparison approach is more restricted to simple two sample comparison with normal approximation test because of its poor properties with more complicated design and analysis. On the other hand, the generalized historical control comparison approach may have more flexible properties when the variability of the margin delta is indeed negligibly small.
Tsong
Yi
Y
Office of Biostatistics/Office of Translational Sciences, CDER, US FDA, Silver Spring, MD 20993-0002, USA. yi.tong@fda.hhs.gov
Chen
Wen-Jen
WJ
D016001:Confidence Intervals; D018849:Controlled Clinical Trials as Topic / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D004341:Drug Evaluation; D006801:Humans; D015233:Models, Statistical; D012107:Research Design / Q000592:standards / Q000706:statistics & numerical data*; D018401:Sample Size