NDLI: Evaluation of bootstrap methods for estimating uncertainty of parameters in nonlinear mixed-effects models: a simulation study in population pharmacokinetics

Content Provider	Springer Nature Link
Author	Thai, Hoai Thu Mentré, France Holford, Nicholas H. G. Veyrat Follet, Christine Comets, Emmanuelle
Copyright Year	2013
Abstract	Bootstrap methods are used in many disciplines to estimate the uncertainty of parameters, including multi-level or linear mixed-effects models. Residual-based bootstrap methods which resample both random effects and residuals are an alternative approach to case bootstrap, which resamples the individuals. Most PKPD applications use the case bootstrap, for which software is available. In this study, we evaluated the performance of three bootstrap methods (case bootstrap, nonparametric residual bootstrap and parametric bootstrap) by a simulation study and compared them to that of an asymptotic method (Asym) in estimating uncertainty of parameters in nonlinear mixed-effects models (NLMEM) with heteroscedastic error. This simulation was conducted using as an example of the PK model for aflibercept, an anti-angiogenic drug. As expected, we found that the bootstrap methods provided better estimates of uncertainty for parameters in NLMEM with high nonlinearity and having balanced designs compared to the Asym, as implemented in MONOLIX. Overall, the parametric bootstrap performed better than the case bootstrap as the true model and variance distribution were used. However, the case bootstrap is faster and simpler as it makes no assumptions on the model and preserves both between subject and residual variability in one resampling step. The performance of the nonparametric residual bootstrap was found to be limited when applying to NLMEM due to its failure to reflate the variance before resampling in unbalanced designs where the Asym and the parametric bootstrap performed well and better than case bootstrap even with stratification.
Starting Page	15
Ending Page	33
Page Count	19
File Format	PDF
ISSN	1567567X
Journal	Journal of Pharmacokinetics and Pharmacodynamics
Volume Number	41
Issue Number	1
e-ISSN	15738744
Language	English
Publisher	Springer US
Publisher Date	2013-12-08
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bootstrap Nonlinear mixed-effects models Pharmacokinetics Uncertainty of parameters MONOLIX Pharmacology/Toxicology Pharmacy Veterinary Medicine Biomedical Engineering Biochemistry
Content Type	Text
Resource Type	Article
Subject	Pharmacology

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