Some alternatives to asymptotic tests for the analysis of pharmacogenetic data using nonlinear mixed effects models.: Alternatives to Asymptotic Tests in NLMEM: an Application to Pharmacogenetics

Julie Bertrand 1, * Emmanuelle Comets 1 Marylore Chenel 2 France Mentré 1
* Auteur correspondant
1 Modèles et méthodes de l'évaluation thérapeutique des maladies chroniques
2 Institut de Recherches Internationales Sevier
Abstract : Nonlinear mixed effects models allow investigating individual differences in drug concentration profiles (pharmacokinetics) and responses. Pharmacogenetics focuses on the genetic component of this variability. Two tests often used to detect a gene effect on a pharmacokinetic parameter are (1) the Wald test, assessing whether estimates for the gene effect are significantly different from 0 and (2) the likelihood ratio test comparing models with and without the genetic effect. Because those asymptotic tests show inflated type I error on small sample size and/or with unevenly distributed genotypes, we develop two alternatives and evaluate them by means of a simulation study. First, we assess the performance of the permutation test using the Wald and the likelihood ratio statistics. Second, for the Wald test we propose the use of the F-distribution with four different values for the denominator degrees of freedom. We also explore the influence of the estimation algorithm using both the first-order conditional estimation with interaction linearization-based algorithm and the stochastic approximation expectation maximization algorithm. We apply these methods to the analysis of the pharmacogenetics of indinavir in HIV patients recruited in the COPHAR2-ANRS 111 trial. Results of the simulation study show that the permutation test seems appropriate but at the cost of an additional computational burden. One of the four F-distribution-based approaches provides a correct type I error estimate for the Wald test and should be further investigated.
Keywords : Pharmacogenetics F-distribution based approach First-order approximation Nonlinear mixed effects models Permutation tests Pharmacogenetics.
Type de document :
Article dans une revue
Biometrics, Wiley, 2012, 68 (1), pp.146-55. 〈10.1111/j.1541-0420.2011.01665.x〉
Liste complète des métadonnées

Littérature citée [25 références]  Voir  Masquer  Télécharger
http://www.hal.inserm.fr/inserm-00709820
Contributeur : Thu Thuy Nguyen <>
Soumis le : mardi 19 juin 2012 - 15:01:52
Dernière modification le : mardi 11 octobre 2016 - 13:56:34
Document(s) archivé(s) le : jeudi 20 septembre 2012 - 02:35:36

Fichier

Bertrand_210611_BiomMeth.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

USPC

Citation

Julie Bertrand, Emmanuelle Comets, Marylore Chenel, France Mentré. Some alternatives to asymptotic tests for the analysis of pharmacogenetic data using nonlinear mixed effects models.: Alternatives to Asymptotic Tests in NLMEM: an Application to Pharmacogenetics. Biometrics, Wiley, 2012, 68 (1), pp.146-55. 〈10.1111/j.1541-0420.2011.01665.x〉. 〈inserm-00709820〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

272

Téléchargements de fichiers

243

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD