Towards model-informed precision dosing of piperacillin: multicenter systematic external evaluation of pharmacokinetic models in critically ill adults with a focus on Bayesian forecasting

URN to cite this document:

urn:nbn:de:bvb:355-epub-544879 Copy

DOI to cite this document:

10.5283/epub.54487 Copy

Greppmair, Sebastian ; Brinkmann, Alexander ; Roehr, Anka ; Frey, Otto ; Hagel, Stefan ; Dorn, Christoph ; Marsot, Amélie ; El-Haffaf, Ibrahim ; Zoller, Michael ; Saller, Thomas ; Zander, Johannes ; Schatz, Lea Marie ; Scharf, Christina ; Briegel, Josef ; Minichmayr, Iris K. ; Wicha, Sebastian G. ; Liebchen, Uwe

License: Creative Commons Attribution Non-commercial 4.0 PDF - Published Version (1MB)

Date of publication of this fulltext: 20 Jul 2023 07:38

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Details

Item type:	Article
Open Access Type:	CC-License
Journal or Publication Title:	Intensive Care Medicine
Publisher:	Springer
Date:	13 July 2023
Institutions:	Chemistry and Pharmacy > Institute of Pharmacy > Group Clinical Pharmacy (Dr. Dorn)
Projects (Historical):	DFG 504995322
Identification Number:	Value Type 10.1007/s00134-023-07154-0 DOI
Dewey Decimal Classification:	600 Technology > 615 Pharmacy
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Yes
Item ID:	54487

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Abstract

Purpose: Inadequate piperacillin (PIP) exposure in intensive care unit (ICU) patients threatens therapeutic success. Model-informed precision dosing (MIPD) might be promising to individualize dosing; however, the transferability of published models to external populations is uncertain. This study aimed to externally evaluate the available PIP population pharmacokinetic (PopPK) models. Methods: ...

Abstract

Purpose: Inadequate piperacillin (PIP) exposure in intensive care unit (ICU) patients threatens therapeutic success. Model-informed precision dosing (MIPD) might be promising to individualize dosing; however, the transferability of published models to external populations is uncertain. This study aimed to externally evaluate the available PIP population pharmacokinetic (PopPK) models.

Methods: A multicenter dataset of 561 ICU patients (11 centers/3654 concentrations) was used for the evaluation of 24 identified models. Model performance was investigated for a priori (A) predictions, i.e., considering dosing records and patient characteristics only, and for Bayesian forecasting, i.e., additionally including the first (B1) or first and second (B2) therapeutic drug monitoring (TDM) samples per patient. Median relative prediction error (MPE) [%] and median absolute relative prediction error (MAPE) [%] were calculated to quantify accuracy and precision.

Results: The evaluation revealed a large inter-model variability (A: MPE - 135.6-78.3% and MAPE 35.7-135.6%). Integration of TDM data improved all model predictions (B1/B2 relative improvement vs. A: |MPE|median_all_models 45.1/67.5%; MAPEmedian_all_models 29/39%). The model by Kim et al. was identified to be most appropriate for the total dataset (A/B1/B2: MPE - 9.8/- 5.9/- 0.9%; MAPE 37/27.3/23.7%), Udy et al. performed best in patients receiving intermittent infusion, and Klastrup et al. best predicted patients receiving continuous infusion. Additional evaluations stratified by sex and renal replacement therapy revealed further promising models.

Conclusion: The predictive performance of published PIP models in ICU patients varied considerably, highlighting the relevance of appropriate model selection for MIPD. Our differentiated external evaluation identified specific models suitable for clinical use, especially in combination with TDM.

Keywords: Intensive care medicine; Model-informed precision dosing; Pharmacokinetics/pharmacodynamics; Piperacillin; Therapeutic drug monitoring.

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Metadata last modified: 20 Jul 2023 07:38

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