Home > Research > Publications & Outputs > Comparing sampling methods for pharmacokinetic ...

Electronic data

  • Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters

    Rights statement: This is the peer reviewed version of the following article: Barnett HY, Geys H, Jacobs T, Jaki T. Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters. Statistics in Medicine. 2017;36:4301–4315. https://doi.org/10.1002/sim.7436 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.7436/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

    Accepted author manuscript, 349 KB, PDF document

    Available under license: CC BY-NC

Links

Text available via DOI:

View graph of relations

Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters

Research output: Contribution to journalJournal articlepeer-review

Published

Standard

Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters. / Barnett, Helen Yvette; Geys, Helena; Jacobs, Tom; Jaki, Thomas.

In: Statistics in Medicine, Vol. 36, No. 27, 30.11.2017, p. 4301-4315.

Research output: Contribution to journalJournal articlepeer-review

Harvard

APA

Vancouver

Author

Barnett, Helen Yvette ; Geys, Helena ; Jacobs, Tom ; Jaki, Thomas. / Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters. In: Statistics in Medicine. 2017 ; Vol. 36, No. 27. pp. 4301-4315.

Bibtex

@article{b791704b512a4e90b83aa82f57875c00,
title = "Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters",
abstract = "Pharmacokinetic studies aim to study how a compound is absorbed, distributed, metabolised, and excreted. The concentration of the compound in the blood or plasma is measured at different time points after administration and pharmacokinetic parameters such as the area under the curve (AUC) or maximum concentration (C max ) are derived from the resulting concentration time profile. In this paper, we want to compare different methods for collecting concentration measurements (traditional sampling versus microsampling) on the basis of these derived parameters. We adjust and evaluate an existing method for testing superiority of multiple derived parameters that accounts for model uncertainty. We subsequently extend the approach to allow testing for equivalence. We motivate the methods through an illustrative example and evaluate the performance using simulations. The extensions show promising results for application to the desired setting.",
keywords = "comparing sampling methods, derived parameters, equivalence testing, multiple comparison, pharmacokinetic studies, simultaneous inference",
author = "Barnett, {Helen Yvette} and Helena Geys and Tom Jacobs and Thomas Jaki",
note = "This is the peer reviewed version of the following article: Barnett HY, Geys H, Jacobs T, Jaki T. Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters. Statistics in Medicine. 2017;36:4301–4315. https://doi.org/10.1002/sim.7436 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.7436/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.",
year = "2017",
month = nov,
day = "30",
doi = "10.1002/sim.7436",
language = "English",
volume = "36",
pages = "4301--4315",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "John Wiley and Sons Ltd",
number = "27",

}

RIS

TY - JOUR

T1 - Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters

AU - Barnett, Helen Yvette

AU - Geys, Helena

AU - Jacobs, Tom

AU - Jaki, Thomas

N1 - This is the peer reviewed version of the following article: Barnett HY, Geys H, Jacobs T, Jaki T. Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters. Statistics in Medicine. 2017;36:4301–4315. https://doi.org/10.1002/sim.7436 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.7436/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2017/11/30

Y1 - 2017/11/30

N2 - Pharmacokinetic studies aim to study how a compound is absorbed, distributed, metabolised, and excreted. The concentration of the compound in the blood or plasma is measured at different time points after administration and pharmacokinetic parameters such as the area under the curve (AUC) or maximum concentration (C max ) are derived from the resulting concentration time profile. In this paper, we want to compare different methods for collecting concentration measurements (traditional sampling versus microsampling) on the basis of these derived parameters. We adjust and evaluate an existing method for testing superiority of multiple derived parameters that accounts for model uncertainty. We subsequently extend the approach to allow testing for equivalence. We motivate the methods through an illustrative example and evaluate the performance using simulations. The extensions show promising results for application to the desired setting.

AB - Pharmacokinetic studies aim to study how a compound is absorbed, distributed, metabolised, and excreted. The concentration of the compound in the blood or plasma is measured at different time points after administration and pharmacokinetic parameters such as the area under the curve (AUC) or maximum concentration (C max ) are derived from the resulting concentration time profile. In this paper, we want to compare different methods for collecting concentration measurements (traditional sampling versus microsampling) on the basis of these derived parameters. We adjust and evaluate an existing method for testing superiority of multiple derived parameters that accounts for model uncertainty. We subsequently extend the approach to allow testing for equivalence. We motivate the methods through an illustrative example and evaluate the performance using simulations. The extensions show promising results for application to the desired setting.

KW - comparing sampling methods

KW - derived parameters

KW - equivalence testing

KW - multiple comparison

KW - pharmacokinetic studies

KW - simultaneous inference

U2 - 10.1002/sim.7436

DO - 10.1002/sim.7436

M3 - Journal article

VL - 36

SP - 4301

EP - 4315

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 27

ER -