Cargando…

Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients

BACKGROUND AND OBJECTIVE: Previous pharmacokinetic (PK) studies of ciprofloxacin in intensive care (ICU) patients have shown large differences in estimated PK parameters, suggesting that further investigation is needed for this population. Hence, we performed a pooled population PK analysis of cipro...

Descripción completa

Detalles Bibliográficos
Autores principales: Guo, Tingjie, Abdulla, Alan, Koch, Birgit C. P., van Hasselt, Johan G. C., Endeman, Henrik, Schouten, Jeroen A., Elbers, Paul W. G., Brüggemann, Roger J. M., van Hest, Reinier M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249715/
https://www.ncbi.nlm.nih.gov/pubmed/35262847
http://dx.doi.org/10.1007/s40262-022-01114-5
_version_ 1784739647785533440
author Guo, Tingjie
Abdulla, Alan
Koch, Birgit C. P.
van Hasselt, Johan G. C.
Endeman, Henrik
Schouten, Jeroen A.
Elbers, Paul W. G.
Brüggemann, Roger J. M.
van Hest, Reinier M.
author_facet Guo, Tingjie
Abdulla, Alan
Koch, Birgit C. P.
van Hasselt, Johan G. C.
Endeman, Henrik
Schouten, Jeroen A.
Elbers, Paul W. G.
Brüggemann, Roger J. M.
van Hest, Reinier M.
author_sort Guo, Tingjie
collection PubMed
description BACKGROUND AND OBJECTIVE: Previous pharmacokinetic (PK) studies of ciprofloxacin in intensive care (ICU) patients have shown large differences in estimated PK parameters, suggesting that further investigation is needed for this population. Hence, we performed a pooled population PK analysis of ciprofloxacin after intravenous administration using individual patient data from three studies. Additionally, we studied the PK differences between these studies through a post-hoc analysis. METHODS: Individual patient data from three studies (study 1, 2, and 3) were pooled. The pooled data set consisted of 1094 ciprofloxacin concentration–time data points from 140 ICU patients. Nonlinear mixed-effects modeling was used to develop a population PK model. Covariates were selected following a stepwise covariate modeling procedure. To analyze PK differences between the three original studies, random samples were drawn from the posterior distribution of individual PK parameters. These samples were used for a simulation study comparing PK exposure and the percentage of target attainment between patients of these studies. RESULTS: A two-compartment model with first-order elimination best described the data. Inter-individual variability was added to the clearance, central volume, and peripheral volume. Inter-occasion variability was added to clearance only. Body weight was added to all parameters allometrically. Estimated glomerular filtration rate on ciprofloxacin clearance was identified as the only covariate relationship resulting in a drop in inter-individual variability of clearance from 58.7 to 47.2%. In the post-hoc analysis, clearance showed the highest deviation between the three studies with a coefficient of variation of 14.3% for posterior mean and 24.1% for posterior inter-individual variability. The simulation study showed that following the same dose regimen of 400 mg three times daily, the area under the concentration–time curve of study 3 was the highest with a mean area under the concentration–time curve at 24 h of 58 mg·h/L compared with that of 47.7 mg·h/L for study 1 and 47.6 mg·h/L for study 2. Similar differences were also observed in the percentage of target attainment, defined as the ratio of area under the concentration–time curve at 24 h and the minimum inhibitory concentration. At the epidemiological cut-off minimum inhibitory concentration of Pseudomonas aeruginosa of 0.5 mg/L, percentage of target attainment was only 21%, 18%, and 38% for study 1, 2, and 3, respectively. CONCLUSIONS: We developed a population PK model of ciprofloxacin in ICU patients using pooled data of individual patients from three studies. A simple ciprofloxacin dose recommendation for the entire ICU population remains challenging owing to the PK differences within ICU patients, hence dose individualization may be needed for the optimization of ciprofloxacin treatment.
format Online
Article
Text
id pubmed-9249715
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-92497152022-07-03 Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients Guo, Tingjie Abdulla, Alan Koch, Birgit C. P. van Hasselt, Johan G. C. Endeman, Henrik Schouten, Jeroen A. Elbers, Paul W. G. Brüggemann, Roger J. M. van Hest, Reinier M. Clin Pharmacokinet Original Research Article BACKGROUND AND OBJECTIVE: Previous pharmacokinetic (PK) studies of ciprofloxacin in intensive care (ICU) patients have shown large differences in estimated PK parameters, suggesting that further investigation is needed for this population. Hence, we performed a pooled population PK analysis of ciprofloxacin after intravenous administration using individual patient data from three studies. Additionally, we studied the PK differences between these studies through a post-hoc analysis. METHODS: Individual patient data from three studies (study 1, 2, and 3) were pooled. The pooled data set consisted of 1094 ciprofloxacin concentration–time data points from 140 ICU patients. Nonlinear mixed-effects modeling was used to develop a population PK model. Covariates were selected following a stepwise covariate modeling procedure. To analyze PK differences between the three original studies, random samples were drawn from the posterior distribution of individual PK parameters. These samples were used for a simulation study comparing PK exposure and the percentage of target attainment between patients of these studies. RESULTS: A two-compartment model with first-order elimination best described the data. Inter-individual variability was added to the clearance, central volume, and peripheral volume. Inter-occasion variability was added to clearance only. Body weight was added to all parameters allometrically. Estimated glomerular filtration rate on ciprofloxacin clearance was identified as the only covariate relationship resulting in a drop in inter-individual variability of clearance from 58.7 to 47.2%. In the post-hoc analysis, clearance showed the highest deviation between the three studies with a coefficient of variation of 14.3% for posterior mean and 24.1% for posterior inter-individual variability. The simulation study showed that following the same dose regimen of 400 mg three times daily, the area under the concentration–time curve of study 3 was the highest with a mean area under the concentration–time curve at 24 h of 58 mg·h/L compared with that of 47.7 mg·h/L for study 1 and 47.6 mg·h/L for study 2. Similar differences were also observed in the percentage of target attainment, defined as the ratio of area under the concentration–time curve at 24 h and the minimum inhibitory concentration. At the epidemiological cut-off minimum inhibitory concentration of Pseudomonas aeruginosa of 0.5 mg/L, percentage of target attainment was only 21%, 18%, and 38% for study 1, 2, and 3, respectively. CONCLUSIONS: We developed a population PK model of ciprofloxacin in ICU patients using pooled data of individual patients from three studies. A simple ciprofloxacin dose recommendation for the entire ICU population remains challenging owing to the PK differences within ICU patients, hence dose individualization may be needed for the optimization of ciprofloxacin treatment. Springer International Publishing 2022-03-09 2022 /pmc/articles/PMC9249715/ /pubmed/35262847 http://dx.doi.org/10.1007/s40262-022-01114-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research Article
Guo, Tingjie
Abdulla, Alan
Koch, Birgit C. P.
van Hasselt, Johan G. C.
Endeman, Henrik
Schouten, Jeroen A.
Elbers, Paul W. G.
Brüggemann, Roger J. M.
van Hest, Reinier M.
Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients
title Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients
title_full Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients
title_fullStr Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients
title_full_unstemmed Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients
title_short Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients
title_sort pooled population pharmacokinetic analysis for exploring ciprofloxacin pharmacokinetic variability in intensive care patients
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249715/
https://www.ncbi.nlm.nih.gov/pubmed/35262847
http://dx.doi.org/10.1007/s40262-022-01114-5
work_keys_str_mv AT guotingjie pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT abdullaalan pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT kochbirgitcp pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT vanhasseltjohangc pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT endemanhenrik pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT schoutenjeroena pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT elberspaulwg pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT bruggemannrogerjm pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT vanhestreinierm pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients
AT pooledpopulationpharmacokineticanalysisforexploringciprofloxacinpharmacokineticvariabilityinintensivecarepatients