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

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.
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Biometrics, Wiley, 2012, 68 (1), pp.146-55. <10.1111/j.1541-0420.2011.01665.x>
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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>

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