PMID: identifiant
de la référence Pubmed : |
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 (19266541) |
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| titre : |
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Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model. |
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| auteur(s) : |
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Caroline Bazzoli ( ) 1, Sylvie Retout1, France Mentré1 |
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| laboratoire : |
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| résumé : |
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We focus on the Fisher information matrix used for design evaluation and optimization in nonlinear mixed effects multiple response models. We evaluate the appropriateness of its expression computed by linearization as proposed for a single response model. Using a pharmacokinetic-pharmacodynamic (PKPD) example, we first compare the computation of the Fisher information matrix with approximation to one derived from the observed matrix on a large simulation using the stochastic approximation expectation-maximization algorithm (SAEM). The expression of the Fisher information matrix for multiple responses is also evaluated by comparison with the empirical information obtained through a replicated simulation study using the first-order linearization estimation methods implemented in the NONMEM software (first-order (FO), first-order conditional estimate (FOCE)) and the SAEM algorithm in the MONOLIX software. The predicted errors given by the approximated information matrix are close to those given by the information matrix obtained without linearization using SAEM and to the empirical ones obtained with FOCE and SAEM. The simulation study also illustrates the accuracy of both FOCE and SAEM estimation algorithms when jointly modelling multiple responses and the major limitations of the FO method. This study highlights the appropriateness of the approximated Fisher information matrix for multiple responses, which is implemented in PFIM 3.0, an extension of the R function PFIM dedicated to design evaluation and optimization. It also emphasizes the use of this computing tool for designing population multiple response studies, as for instance in PKPD studies or in PK studies including the modelling of the PK of a drug and its active metabolite. |
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| domaine : |
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langue du texte
intégral : |
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Anglais |
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| ISSN : |
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0277-6715 |
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| type de publication : |
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Articles dans des revues avec comité de lecture |
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| DOI : |
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10.1002/sim.3573 |
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| journal : |
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| Statistics in Medicine (Stat Med) |
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John Wiley and Sons |
| ISSN |
0277-6715 (eISSN : 1097-0258) |
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| Audience : |
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internationale |
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| date de publication : |
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30/06/2009 |
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date de publication
électronique : |
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05/03/2009 |
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| volume : |
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28 |
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| numéro : |
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14 |
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| page, identifiant, ... : |
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1940-56 |
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| mots-clés auteur : |
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nonlinear mixed effects models – multiple responses – Fisher information matrix – population design – first-order approximation – PFIM |
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| Descripteur(s) MeSH : |
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Algorithms – Analysis of Variance – Bias (Epidemiology) – Computer Simulation – Humans – Likelihood Functions – Models – Statistical – Nonlinear Dynamics – Pharmacokinetics – Pharmacological Processes – Software |
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| contrat, financement : |
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Part of this work was supported by a grant from F. Hoffmann La Roche Ltd, Basel, Switzerland. |
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