Detecting and Accounting for Violations of the Constancy Assumption in Noninferiority Clinical Trials

• Activity Number: 13
• Type: Invited
• Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Section on Medical Devices and Diagnostics
• Author(s): Joe Koopmeiners* and Brian Hobbs
• Companies: University of Minnesota and MD Anderson Cancer Center

Abstract

In a non-inferiority clinical trial, the experimental treatment (ET) is compared to an active comparator (AC) with the primary objective of showing that the ET retains a pre-specified proportion of the effect of the AC, as represented by the non-inferiority margin. Valid inference requires the constancy assumption, which assumes that the effect of the AC is consistent with the effect that was observed in previous trials. Violations of the constancy assumption can result in a dramatic increase in the rate of incorrectly concluding non-inferiority in the presence of ineffective or even harmful treatment. We illustrate how Bayesian hierarchical modeling can be used to facilitate multi-source smoothing of the data from the current trial with the data from historical studies, enabling direct probabilistic evaluation of the constancy assumption. We then show how this result can be used to adapt the non-inferiority margin when the constancy assumption is violated and present simulation results illustrating that our method controls the type-I error rate when the constancy assumption is violated, while retaining the power of the standard approach when the constancy assumption holds.