Concentration–QTc analysis for single arm studies

A comprehensive regulatory and industry review of modeling and simulation practices in oncology clinical drug development

“…In addition, the lack of placebo data introduces diurnal fluctuation in QTc as a potential confounding factor for drug effect on QTc intervals [ 69 ]. The collection of time-matched baseline (i.e., at the same time points to be collected post-dose) in order to account for diurnal fluctuation has been successfully implemented for C-QT analysis of single-arm trials [ 65 , 68 , 70 ]; where only a pre-dose baseline was available, the inclusion of categorical time effects in the C-QTc model has recently been proposed [ 71 ]. Where a compound is known to substantially affect HR (i.e., mean change > 10 bpm), the inclusion of a time-matched baseline can allow a patient-specific HR correction to be calculated from baseline QT/RR data, although consensus has not been achieved on the optimal approach [ 68 , 72 ].…”

QTc interval analysis—an ever-evolving endeavor

“…Ferber et al [22] demonstrate that hysteresis can reduce the power to detect a positive QT prolongation signal and then present a novel metric to assess QT interval hysteresis that may be used in lieu of visual inspection. Heinrich et al [23] take a different approach to assess hysteresis through use of an indirect response model between drug concentrations and drug effect. Orihashi, Ohwada, and Kumagai [24] present alternative models to the white paper model for single arm studies where placebo data might not be available.…”