Comparison of model-based tests and selection strategies to detect genetic polymorphisms influencing pharmacokinetic parameters. - Archive ouverte HAL Access content directly
Journal Articles Journal of Biopharmaceutical Statistics Year : 2008

Comparison of model-based tests and selection strategies to detect genetic polymorphisms influencing pharmacokinetic parameters.

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Abstract

We evaluate by simulation three model-based methods to test the influence of a single nucleotide polymorphism on a pharmacokinetic parameter of a drug: analysis of variance (ANOVA) on the empirical Bayes estimates of the individual parameters, likelihood ratio test between models with and without genetic covariate, and Wald tests on the parameters of the model with covariate. Analyses are performed using the FO and FOCE method implemented in the NONMEM software. We compare several approaches for model selection based on tests and global criteria. We illustrate the results with pharmacokinetic data on indinavir from HIV-positive patients included in COPHAR 2-ANRS 111 to study the gene effect prospectively. Only the tests based on the EBE obtain an empirical type I error close to the expected 5%. The approximation made with the FO algorithm results in a significant inflation of the type I error of the LRT and Wald tests.
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Dates and versions

inserm-00339183 , version 1 (17-11-2009)

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Julie Bertrand, Emmanuelle Comets, France Mentre. Comparison of model-based tests and selection strategies to detect genetic polymorphisms influencing pharmacokinetic parameters.. Journal of Biopharmaceutical Statistics, 2008, 18 (6), pp.1084-102. ⟨10.1080/10543400802369012⟩. ⟨inserm-00339183⟩
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