Some alternatives to asymptotic tests for the analysis of pharmacogenetic data using nonlinear mixed effects models. - Inserm - Institut national de la santé et de la recherche médicale Accéder directement au contenu
Article Dans Une Revue Biometrics Année : 2012

Some alternatives to asymptotic tests for the analysis of pharmacogenetic data using nonlinear mixed effects models.

Résumé

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.
Fichier principal
Vignette du fichier
Bertrand_210611_BiomMeth.pdf (238.51 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

inserm-00709820 , version 1 (19-06-2012)

Identifiants

Citer

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, 2012, 68 (1), pp.146-55. ⟨10.1111/j.1541-0420.2011.01665.x⟩. ⟨inserm-00709820⟩

Collections

INSERM UNIV-PARIS7
182 Consultations
472 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More