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Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models
Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5419648/ https://www.ncbi.nlm.nih.gov/pubmed/28475651 http://dx.doi.org/10.1371/journal.pone.0177324 |
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author | Gomes, Anna van der Wijk, Lars Proost, Johannes H. Sinha, Bhanu Touw, Daan J. |
author_facet | Gomes, Anna van der Wijk, Lars Proost, Johannes H. Sinha, Bhanu Touw, Daan J. |
author_sort | Gomes, Anna |
collection | PubMed |
description | Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1) creating an optimal model for endocarditis patients; and 2) assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE) and Median Absolute Prediction Error (MDAPE) were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients) with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358) renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076) L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68%) as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37%) and standard (MDPE -0.90%, MDAPE 4.82%) models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to avoid potential underdosing of gentamicin in endocarditis patients. |
format | Online Article Text |
id | pubmed-5419648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54196482017-05-14 Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models Gomes, Anna van der Wijk, Lars Proost, Johannes H. Sinha, Bhanu Touw, Daan J. PLoS One Research Article Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1) creating an optimal model for endocarditis patients; and 2) assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE) and Median Absolute Prediction Error (MDAPE) were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients) with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358) renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076) L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68%) as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37%) and standard (MDPE -0.90%, MDAPE 4.82%) models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to avoid potential underdosing of gentamicin in endocarditis patients. Public Library of Science 2017-05-05 /pmc/articles/PMC5419648/ /pubmed/28475651 http://dx.doi.org/10.1371/journal.pone.0177324 Text en © 2017 Gomes et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Gomes, Anna van der Wijk, Lars Proost, Johannes H. Sinha, Bhanu Touw, Daan J. Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models |
title | Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models |
title_full | Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models |
title_fullStr | Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models |
title_full_unstemmed | Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models |
title_short | Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models |
title_sort | pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: model development and validation of existing models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5419648/ https://www.ncbi.nlm.nih.gov/pubmed/28475651 http://dx.doi.org/10.1371/journal.pone.0177324 |
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