NDLI: Evaluation of Approaches to Deal with Low-Frequency Nuisance Covariates in Population Pharmacokinetic Analyses

Content Provider	Springer Nature Link
Author	Lagishetty, Chakradhar V. Duffull, Stephen B.
Copyright Year	2015
Abstract	Clinical studies include occurrences of rare variables, like genotypes, which due to their frequency and strength render their effects difficult to estimate from a dataset. Variables that influence the estimated value of a model-based parameter are termed covariates. It is often difficult to determine if such an effect is significant, since type I error can be inflated when the covariate is rare. Their presence may have either an insubstantial effect on the parameters of interest, hence are ignorable, or conversely they may be influential and therefore non-ignorable. In the case that these covariate effects cannot be estimated due to power and are non-ignorable, then these are considered nuisance, in that they have to be considered but due to type 1 error are of limited interest. This study assesses methods of handling nuisance covariate effects. The specific objectives include (1) calibrating the frequency of a covariate that is associated with type 1 error inflation, (2) calibrating its strength that renders it non-ignorable and (3) evaluating methods for handling these non-ignorable covariates in a nonlinear mixed effects model setting. Type 1 error was determined for the Wald test. Methods considered for handling the nuisance covariate effects were case deletion, Box-Cox transformation and inclusion of a specific fixed effects parameter. Non-ignorable nuisance covariates were found to be effectively handled through addition of a fixed effect parameter.
Starting Page	1388
Ending Page	1394
Page Count	7
File Format	PDF
ISSN	12341234
Journal	The AAPS Journal
Volume Number	17
Issue Number	6
e-ISSN	15507416
Language	English
Publisher	Springer US
Publisher Date	2015-06-26
Publisher Institution	American Association of Pharmaceutical Scientists
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Pharmacology/Toxicology Biochemistry Biotechnology Pharmacy
Content Type	Text
Resource Type	Article

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