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Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection

Polymyxin B (PMB) is the final option for treating multidrug-resistant Gram-negative bacterial infections. The acceptable pharmacokinetic/pharmacodynamic target is an area under the concentration–time curve across 24 h at a steady state (AUC(ss,24h)) of 50–100 mg·h/L. The limited sampling strategy (...

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Autores principales: Li, Xueyong, Zhang, Bingqing, Cheng, Yu, Chen, Maohua, Lin, Hailing, Huang, Binglin, Que, Wancai, Liu, Maobai, Zhou, Lili, Weng, Qinyong, Zhang, Hui, Qiu, Hongqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698835/
https://www.ncbi.nlm.nih.gov/pubmed/36365141
http://dx.doi.org/10.3390/pharmaceutics14112323
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author Li, Xueyong
Zhang, Bingqing
Cheng, Yu
Chen, Maohua
Lin, Hailing
Huang, Binglin
Que, Wancai
Liu, Maobai
Zhou, Lili
Weng, Qinyong
Zhang, Hui
Qiu, Hongqiang
author_facet Li, Xueyong
Zhang, Bingqing
Cheng, Yu
Chen, Maohua
Lin, Hailing
Huang, Binglin
Que, Wancai
Liu, Maobai
Zhou, Lili
Weng, Qinyong
Zhang, Hui
Qiu, Hongqiang
author_sort Li, Xueyong
collection PubMed
description Polymyxin B (PMB) is the final option for treating multidrug-resistant Gram-negative bacterial infections. The acceptable pharmacokinetic/pharmacodynamic target is an area under the concentration–time curve across 24 h at a steady state (AUC(ss,24h)) of 50–100 mg·h/L. The limited sampling strategy (LSS) is useful for predicting AUC values. However, establishing an LSS is a time-consuming process requiring a relatively dense sampling of patients. Further, given the variability among different centers, the predictability of LSSs is frequently questioned when it is extrapolated to other clinical centers. Currently, limited data are available on a reliable PMB LSS for estimating AUC(ss,24h). This study assessed and validated the practicability of LSSs established in the literature based on data from our center to provide reliable and ready-made PMB LSSs for laboratories performing therapeutic drug monitoring (TDM) of PMB. The influence of infusion and sampling time errors on predictability was also explored to obtain the optimal time points for routine PMB TDM. Using multiple regression analysis, PMB LSSs were generated from a model group of 20 patients. A validation group (10 patients) was used to validate the established LSSs. PMB LSSs from two published studies were validated using a dataset of 30 patients from our center. A population pharmacokinetic model was established to simulate the individual plasma concentration profiles for each infusion and sampling time error regimen. Pharmacokinetic data obtained from the 30 patients were fitted to a two-compartment model. Infusion and sampling time errors observed in real-world clinical practice could considerably affect the predictability of PMB LSSs. Moreover, we identified specific LSSs to be superior in predicting PMB AUC(ss,24h) based on different infusion times. We also discovered that sampling time error should be controlled within −10 to 15 min to obtain better predictability. The present study provides validated PMB LSSs that can more accurately predict PMB AUC(ss,24h) in routine clinical practice, facilitating PMB TDM in other laboratories and pharmacokinetics/pharmacodynamics-based clinical studies in the future.
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spelling pubmed-96988352022-11-26 Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection Li, Xueyong Zhang, Bingqing Cheng, Yu Chen, Maohua Lin, Hailing Huang, Binglin Que, Wancai Liu, Maobai Zhou, Lili Weng, Qinyong Zhang, Hui Qiu, Hongqiang Pharmaceutics Article Polymyxin B (PMB) is the final option for treating multidrug-resistant Gram-negative bacterial infections. The acceptable pharmacokinetic/pharmacodynamic target is an area under the concentration–time curve across 24 h at a steady state (AUC(ss,24h)) of 50–100 mg·h/L. The limited sampling strategy (LSS) is useful for predicting AUC values. However, establishing an LSS is a time-consuming process requiring a relatively dense sampling of patients. Further, given the variability among different centers, the predictability of LSSs is frequently questioned when it is extrapolated to other clinical centers. Currently, limited data are available on a reliable PMB LSS for estimating AUC(ss,24h). This study assessed and validated the practicability of LSSs established in the literature based on data from our center to provide reliable and ready-made PMB LSSs for laboratories performing therapeutic drug monitoring (TDM) of PMB. The influence of infusion and sampling time errors on predictability was also explored to obtain the optimal time points for routine PMB TDM. Using multiple regression analysis, PMB LSSs were generated from a model group of 20 patients. A validation group (10 patients) was used to validate the established LSSs. PMB LSSs from two published studies were validated using a dataset of 30 patients from our center. A population pharmacokinetic model was established to simulate the individual plasma concentration profiles for each infusion and sampling time error regimen. Pharmacokinetic data obtained from the 30 patients were fitted to a two-compartment model. Infusion and sampling time errors observed in real-world clinical practice could considerably affect the predictability of PMB LSSs. Moreover, we identified specific LSSs to be superior in predicting PMB AUC(ss,24h) based on different infusion times. We also discovered that sampling time error should be controlled within −10 to 15 min to obtain better predictability. The present study provides validated PMB LSSs that can more accurately predict PMB AUC(ss,24h) in routine clinical practice, facilitating PMB TDM in other laboratories and pharmacokinetics/pharmacodynamics-based clinical studies in the future. MDPI 2022-10-28 /pmc/articles/PMC9698835/ /pubmed/36365141 http://dx.doi.org/10.3390/pharmaceutics14112323 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Xueyong
Zhang, Bingqing
Cheng, Yu
Chen, Maohua
Lin, Hailing
Huang, Binglin
Que, Wancai
Liu, Maobai
Zhou, Lili
Weng, Qinyong
Zhang, Hui
Qiu, Hongqiang
Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection
title Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection
title_full Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection
title_fullStr Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection
title_full_unstemmed Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection
title_short Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection
title_sort evaluation and validation of the limited sampling strategy of polymyxin b in patients with multidrug-resistant gram-negative infection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698835/
https://www.ncbi.nlm.nih.gov/pubmed/36365141
http://dx.doi.org/10.3390/pharmaceutics14112323
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