Evaluation and application of population pharmacokinetic models for optimising linezolid treatment in non-adherence multidrug-resistant tuberculosis patients.
| Autor: | Li R; Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Centre for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China., Sun F; Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Centre for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China., Feng Z; Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Centre for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China., Zhang Y; Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Centre for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China., Lan Y; Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Centre for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China; Department of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Guizhou, China., Yu H; Department of Infectious Diseases, Hunan University of Medicine General Hospital, Huaihua, Hunan, 418000, China., Li Y; Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Centre for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China. Electronic address: lalaliy@sina.com., Mao J; Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, 200040, China. Electronic address: jmao12@fudan.edu.cn., Zhang W; Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Centre for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; Key Laboratory of Medical Molecular Virology (MOE/MOH), Shanghai Medical College, Fudan University, Shanghai, China. |
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| Jazyk: | angličtina |
| Zdroj: | European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences [Eur J Pharm Sci] 2024 Dec 01; Vol. 203, pp. 106915. Date of Electronic Publication: 2024 Sep 26. |
| DOI: | 10.1016/j.ejps.2024.106915 |
| Abstrakt: | Background: Population pharmacokinetic (popPK) models can optimise linezolid dosage regimens in patients with multidrug-resistant tuberculosis (MDR-TB); however, unknown cross-centre precision and poor adherence remain problematic. This study aimed to assess the predictive ability of published models and use the most suitable model to optimise dosage regimens and manage compliance. Methods: One hundred fifty-eight linezolid plasma concentrations from 27 patients with MDR-TB were used to assess the predictive performance of published models. Prediction-based metrics and simulation-based visual predictive checks were conducted to evaluate predictive ability. Individualised remedial dosing regimens for various delayed scenarios were optimised using the most suitable model and Monte Carlo simulations. The influence of covariates, scheduled dosing intervals, and patient compliance were assessed. Results: Seven popPK models were identified. Body weight and creatinine clearance were the most frequently identified covariates influencing linezolid clearance. The model with the best performance had a median prediction error (PE%) of -1.62 %, median absolute PE of 29.50 %, and percentages of PE within 20 % (F Conclusions: Monte Carlo simulations based on popPK models can propose remedial regimens for delayed doses of linezolid in patients with MDR-TB. Model-based compliance management patterns are useful for balancing efficacy, adverse reactions, and resistance suppression. Competing Interests: Declaration of competing interest There are no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, and no other relationships or activities that could appear to have influenced the submitted work. The authors declare no conflicts of interest. (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.) |
| Databáze: | MEDLINE |
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