A note on the conservativeness of the confidence interval approach for the selection of non-inferiority margin in the two-arm active-control trial.
Compared with placebo-control clinical trials, the interpretation of efficacy results from active-control trials requires more caution. This is because efficacy results from such trials cannot be reliably interpreted without a thorough understanding of the efficacy evidence that formed the basis for the approval of the active control, especially when such drug efficacy is to be established on the basis of clinical evidence from the traditional two-arm active-control clinical equivalence studies as opposed to the multi-arm active control. This is because in addition to over-reliance on the quantification of a clinically irrelevant acceptable margin of inferiority from historical data, such interpretation also depends on cross-trial inference for demonstration of experimental drug effect. We provide a brief overview of some design issues with the traditional two-arm active-control clinical trial and discuss regulators' concern regarding Type I error rate control (with the two most popular methods for the quantification of the non-inferiority margin) in cross-trial demonstration of experimental drug effect. Simulation results are presented to show that the point estimate method provides adequate control of the Type I error rate with > or =75 per cent retention of known active-control effect and that the confidence interval approach is uniformly ultra-conservative. We also report (via a numerical example from real clinical trial data) a couple of potentially less stringent alternative approaches for establishing the non-inferiority of a test drug over a control, which have been used in the past to provide additional efficacy evidence in NDA submission.
Sankoh
Abdul J
AJ
Vertex Pharmaceuticals, Cambridge, MA 02139, USA. abdul_sankoh@vrtx.com
D001702:Biopharmaceutics / Q000379:methods; D003198:Computer Simulation; D016001:Confidence Intervals; D018849:Controlled Clinical Trials as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D004341:Drug Evaluation / Q000379:methods; D006801:Humans; D012107:Research Design