Literature DB >> 27492846

Model averaging inconcentration-QT analyses.

Bernard Sébastien1, David Hoffman2, Clémence Rigaux1, Franck Pellissier3, Jérôme Msihid1.   

Abstract

This article describes how a frequentist model averaging approach can be used for concentration-QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration-QT analyses.
Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Keywords:  concentration-QT analysis; model averaging; model selection; thorough QTc study

Mesh:

Year:  2016        PMID: 27492846     DOI: 10.1002/pst.1766

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  2 in total

1.  Estimation of QT interval prolongation through model-averaging.

Authors:  Peter L Bonate
Journal:  J Pharmacokinet Pharmacodyn       Date:  2017-04-18       Impact factor: 2.745

2.  Comparison of Model Averaging and Model Selection in Dose Finding Trials Analyzed by Nonlinear Mixed Effect Models.

Authors:  Simon Buatois; Sebastian Ueckert; Nicolas Frey; Sylvie Retout; France Mentré
Journal:  AAPS J       Date:  2018-03-29       Impact factor: 4.009

  2 in total

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