Relevance of QT-RR correlations in the assessment of QTc-interval prolongation in clinical trial simulations
Francesco Bellanti (1), Anne Chain (1), Meindert Danhof (1), Oscar Della Pasqua (1, 2)
(1) Division of Pharmacology, Leiden University, Leiden, The Netherlands; (2) GlaxoSmithKline, London, United Kingdom
Objectives: Correction for changes in heart rate is a fundamental step to the evaluation of QTc-interval prolongation. Yet, clinical trial simulations for thorough QT (TQT) studies often rely on approximations to evaluate design factors such as group size. The aim of the investigation was to develop a model-based approach to describe the correlation between QT and RR intervals in healthy volunteers.
Methods: A large pool (339 males and 437 females) of healthy volunteer ECG data has been used for the analysis. Data was split into two subsets to allow for the external validation of the final model. The analysis was performed using a non-linear mixed effects approach using NONMEM VI. Model building selection was based on changes in the objective function (OFV) and goodness of fit plots (GOF). Model validation has been carried out internally (simulations and NPDE) and externally (GOF and NPDE).
Results: Among the different functions used in the evaluation of the QT-RR correlation [1], a power function allowed the best model performance. Age and gender were the only available covariates; gender has been found to be significant both on slope [181(13.5) females and 166(12.8) males] and exponent [0.85(0.13) females; 0.74(0.13) males]. Inter-occasion variability on slope and exponent was also identified as a significant random effect. Distributions of simulated and real QT values were comparable. Goodness of fit plots clearly showed the ability of the model to predict data from a different subset of studies. Parameter estimates were subsequently used as part of a thorough QT study simulation.
Conclusions: The final model allows a reliable and realistic simulation of QT-interval profiles starting from a physiological set of RR values. In the context of clinical trial simulations, the availability of such a model represents a concrete improvement in the evaluation of drug-induced QTc-interval prolongation.
References:
[1] Malik M, Färbom P, Batchvarov V, Hnatkova K, Camm AJ, Relation between QT and RR intervals is highly individual among healthy subjects: implications for heart rate correction of the QT interval. Heart, 2002 Mar;87:220-228.
