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Titolo:
Is mixed effects modeling or naive pooled data analysis preferred for the interpretation of single sample per subject toxicokinetic data?
Autore:
Hing, JP; Woolfrey, SG; Greenslade, D; Wright, PMC;
Indirizzi:
Univ Newcastle Upon Tyne, Dept Anaesthesia, Newcastle Upon Tyne NE1 4LP, Tyne & Wear, England Univ Newcastle Upon Tyne Newcastle Upon Tyne Tyne & Wear England NE1 4LP Sanofi, Alnwick Res Ctr, Alnwick, Northd, England Sanofi Alnwick Northd England Alnwick Res Ctr, Alnwick, Northd, England
Titolo Testata:
JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS
fascicolo: 2, volume: 28, anno: 2001,
pagine: 193 - 210
SICI:
1567-567X(200104)28:2<193:IMEMON>2.0.ZU;2-X
Fonte:
ISI
Lingua:
ENG
Soggetto:
POPULATION PHARMACOKINETIC PARAMETERS; EXPERIMENTAL-DESIGN; SPARSE; POINT;
Keywords:
computer simulations; toxicokinetics; destructive sampling; research study design; mixed effects model;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
11
Recensione:
Indirizzi per estratti:
Indirizzo: Wright, PMC Univ Newcastle Upon Tyne, Royal Victoria Infirm, Dept Anaesthesia, Newcastle Upon Tyne NE1 4LP, Tyne & Wear, England Univ Newcastle Upon Tyne Newcastle Upon Tyne Tyne & Wear England NE1 4LP
Citazione:
J.P. Hing et al., "Is mixed effects modeling or naive pooled data analysis preferred for the interpretation of single sample per subject toxicokinetic data?", J PHARMA PH, 28(2), 2001, pp. 193-210

Abstract

The purpose of this study,vas to evaluate whether mixed effects modeling (MEM) performs better than either noncompartmental or compartmental naive pooled data (NPD) analysis for the interpretation of single sample per subject pharmacokinetic (PK) data. Using PK parameters determined during a toxicokinetic study in rats, we simulated data sets that might emerge from similar experiments. Data sets were simulated with varying numbers of animals at each sampling lime (4-48) and the number of samples taken (1-3) from each individual. Each data set was replicated 50 times and analyzed using severalvariations of MEM that differed in the assumptions made regarding intraindividual error, NPD, and a graphical noncompartmental method. These analysesattempted to retrieve the underlying parameter and covariate effect values. We compared these analysis methods,vith respect to how well the underlying values were retrieved. All analysis methods performed poorly with single sample per subject data hut MEM gave less biased estimates under the simulated conditions used here. MEM performance increased when covariate effects,were sought in the analysis compared with analyses seeking only PK parameters. Decreasing the number of animals used per sampling time from 48 to 16 did not influence the quality of parameter estimates but further reductions (< 16 animals per sampling time) resulted in a reduced proportion of acceptable estimates. Parameter estimate quality improved and worsened with MEM and NPD, respectively, when additional samples were obtained from each individual. Assumptions made regarding the magnitude of intraindividual error were unimportant with single sample per subject data but influenced parameterestimates if more samples were obtained from each individual. MEM is preferable to both NPD and noncompartmental approaches for the analysis of single sample per subject data but even with MEM estimates of clearance are often biased.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 06/04/20 alle ore 08:16:42