Clinical application of vancomycin population pharmacokinetics model in patients with hematological diseases and neutropenia

Fu, Xing; Lin, Long; Huang, Li; Li, Guo

doi:10.1002/bdd.2303

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…Recent evidence suggested the acute kidney injury occurred in 15.4% of vancomycin + meropenem patients [17]. The final PPK model in the present study verified that CL CR was the significant covariate for CL, which is consistent with the findings of previous studies [18][19][20]. Gender, age, or body weight did not significantly affect vancomycin clearance; neither did hepatic function or mechanical ventilator, which is likely due to the narrow ranges of these covariates.…”

Section: Ppk Modelssupporting

confidence: 90%

Individualized Delivery of Vancomycin by Model-Informed Bayesian Dosing Approach to Maintain an AUC24 Target in Critically Ill Patients

Rao,

Guo,

Wei

2023

Chemotherapy

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Introduction: Monitoring of AUC24 was updated recommendation in the guideline for the therapeutic drug monitoring (TDM) of vancomycin in Chinese pharmacological society published in 2020. Vancomycin pharmacokinetic profiles are diverse and unique in critically ill patients because of the drastic variability of the patients’ physiological parameters, while the study for population pharmacokinetic (PPK) models in Chinese critically ill patients has been rarely reported. The objectives of this study were to construct a PPK model to describe the pharmacokinetic characteristics of vancomycin in critically ill patients and to individualize vancomycin dosing by model-informed Bayesian estimation for maintenance of AUC24 target at 400–650 mg h/L recommended by the 2020 guideline. Methods: Vancomycin with different dosing was administered intravenously over 1 h for critically ill patients, TDM was started at 48 h or 72 h since initiation of vancomycin therapy for patients. Blood samples were collected from patients for trough concentrations or Cmax. Vancomycin concentrations were determined by high-performance liquid chromatography method with ultraviolet detection. PPK model was performed using the nonlinear mixed-effect model (NONMEM®). Individual PK parameters for critically ill patients treated with vancomycin were estimated using a post hoc empirical Bayesian method based on the final PPK model. AUC24 was calculated as the total daily dose divided by the clearance (L/h). Results: The PPK of vancomycin was determined by a one-compartment model with creatinine clearance as fixed effects. The PK estimates in the final model generally agreed with the median estimates and were contained within the 95% CI generated from the bootstrap results, indicating good precision and stability in the final model. The visual predictive check plots showed the adequate predictive performance of the final PK model and supported a good model fit. The model-informed Bayesian estimation was used to predict the AUC24 of critically ill patient by the acquired TDM results, and the dosing adjustment by maintenance of AUC24 at 400–650 mg h/L had made a great therapeutic effect for the case. Conclusion: This study established a PPK model of vancomycin in Chinese critically ill patients, and individualized dosing of vancomycin by model-informed Bayesian estimation to maintain an AUC24 target at 400–650 mg h/L has been successfully applied in clinic. This result supports the continued use of model-informed Bayesian estimation to vancomycin treatment in critically ill patients.

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Section: Ppk Modelssupporting

confidence: 90%

Individualized Delivery of Vancomycin by Model-Informed Bayesian Dosing Approach to Maintain an AUC24 Target in Critically Ill Patients

Rao,

Guo,

Wei

2023

Chemotherapy

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Clinical application of vancomycin population pharmacokinetics model in patients with hematological diseases and neutropenia

Lin

Huang

et al. 2021

Biopharm & Drug Disp

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To explore the clinical application of a population pharmacokinetics (PPK) model of vancomycin in patients with hematological diseases and neutropenia. Patients with hematological diseases and neutropenia were included in the PPK model study.Nonlinear mixed effect modeling approach (NONMEM) was used for model establishment. Monte Carlo simulation was carried out. A total of 74 patients were divided into model group and non-model group for clinical application research. The model group was given the initial dose of 1g q8h, and the non-model group was given 1g q12h as an empiric initial dosage. The follow-up dose adjustments were made according to the concentration results. This two-compartment model showed good stability and accuracy. The first trough concentration (C 0 ) and the compliance rate of the first C 0 were much higher in the model group than that in the non-model group (14.30 � 4.73 μg/ml and 59.38% vs. 8.02 � 2.61 μg/ml, 35.71%). Less patients needed dose adjustments and fewer adjustment times in the model group than those in the non-model group (12.50% and 0.13 � 0.34 times vs. 50.00% and 0.61 � 0.66 times). This suggested that for those patients who had a Creatinine clearance rate (CLCR) ≥ 90 ml/min/1.73 m 2 , the initial dose of 1g q8h may help to reach the target C 0 (10∼20 μg/ml) quickly. It also helped to reduce the times and number of patients who need dose adjustments. Our PPK model of vancomycin in patients with hematologic diseases and neutropenia can be used to shorten the time to reach the target concentration and reduce the number of dose adjustments.Clinical trial registration: Not applicable (Retrospective study).

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Selecting the Best Pharmacokinetic Models for a Priori Model-Informed Precision Dosing with Model Ensembling

Agema,

Kocher,

Öztürk

et al. 2024

Clin Pharmacokinet

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Background and Objective When utilizing population pharmacokinetic (popPK) models for a priori dosage individualization, selecting the best model is crucial to obtain adequate doses. We developed and evaluated several model-selection and ensembling methods, using external evaluation on the basis of therapeutic drug monitoring (TDM) samples to identify the best (set of) models per patient for a priori dosage individualization. Methods PK data and models describing both hospitalized patients ( n = 134) receiving continuous vancomycin (26 models) and patients ( n = 92) receiving imatinib in an outpatient setting (12 models) are included. Target attainment of four model-selection methods was compared with standard dosing: the best model based on external validation, uninformed model ensembling, model ensembling using a weighting scheme on the basis of covariate-stratified external evaluation, and model selection using covariates in decision trees that were subsequently ensembled. Results Overall, the use of PK models improved the proportion of patients exposed to concentrations within the therapeutic window for both cohorts. Relative improvement of proportion on target for best model, unweighted, weighted, and decision trees were − 7.0%, 2.3%, 11.4%, and 37.0% (vancomycin method-development); 23.2%, 7.9%, 15.6%, and, 77.2% (vancomycin validation); 40.7%, 50.0%, 59.5%, and 59.5% (imatinib method-development); and 19.0%, 28.5%, 38.0%, and 23.8% (imatinib validation), respectively. Conclusions The best (set of) models per patient for a priori dosage individualization can be identified using a relatively small set of TDM samples as external evaluation. Adequately performing popPK models were identified while also excluding poor-performing models. Dose recommendations resulted in more patients within the therapeutic range for both vancomycin and imatinib. Prospective validation is necessary before clinical implementation. Supplementary Information The online version contains supplementary material available at 10.1007/s40262-024-01425-9.

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Clinical application of vancomycin population pharmacokinetics model in patients with hematological diseases and neutropenia

Cited by 3 publications

References 15 publications

Individualized Delivery of Vancomycin by Model-Informed Bayesian Dosing Approach to Maintain an <i>AUC</i><sub><i>24</i></sub> Target in Critically Ill Patients

Individualized Delivery of Vancomycin by Model-Informed Bayesian Dosing Approach to Maintain an <i>AUC</i><sub><i>24</i></sub> Target in Critically Ill Patients

Clinical application of vancomycin population pharmacokinetics model in patients with hematological diseases and neutropenia

Selecting the Best Pharmacokinetic Models for a Priori Model-Informed Precision Dosing with Model Ensembling

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