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量化联合用药方案对结核病治疗效果和耐多药概率的影响。

Quantifying the impact of drug combination regimens on TB treatment efficacy and multidrug resistance probability.

作者信息

Lin Yi-Jun, Liao Chung-Min

机构信息

Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617, Republic of China.

Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617, Republic of China

出版信息

J Antimicrob Chemother. 2015 Dec;70(12):3273-82. doi: 10.1093/jac/dkv247. Epub 2015 Aug 25.

Abstract

OBJECTIVES

TB patients' non-adherence to the multidrug treatment regimen is thought to be the main cause of the emergence of drug resistance. The purpose of this study was to quantify the impacts of two-drug combination regimens and non-adherence to these regimens on treatment efficacy and drug resistance probability.

METHODS

A drug treatment modelling strategy was developed by incorporating a pharmacokinetic/pharmacodynamic model into a bacterial population dynamic model to explore the dynamics of TB bacilli and evolution of resistance during multidrug combination therapy, with an emphasis on non-adherence. A Hill-equation-based pharmacodynamic model was used to assess the bactericidal efficacy of single drugs and to estimate drug interactions.

RESULTS

Non-adherence to the treatment regimen increased treatment duration by nearly 1.6- and 3.4-fold relative to compliance with treatment. Symptom-based intermittent treatment, a form of non-adherence, might lead to treatment failure and accelerated growth and evolution of resistant mutants, resulting in a dramatically higher probability of 4.17 × 10(-3) (95% CI 2.10 × 10(-4)-1.28 × 10(-2)) for the emergence of MDR TB. Overall, determination of the optimal treatment regimen depended on the different types of medication adherence.

CONCLUSIONS

Our model not only predicts evolutionary dynamics, but also quantifies treatment efficacy. More broadly, our model provides a quantitative framework for improving treatment protocols and establishing an emergence threshold of resistance that can be used to prevent drug resistance.

摘要

目的

结核病患者对多药治疗方案的不依从被认为是耐药性出现的主要原因。本研究的目的是量化两药联合方案以及对这些方案的不依从性对治疗效果和耐药概率的影响。

方法

通过将药代动力学/药效学模型纳入细菌群体动力学模型,开发了一种药物治疗建模策略,以探索多药联合治疗期间结核杆菌的动态变化和耐药性演变,重点关注不依从情况。基于希尔方程的药效学模型用于评估单一药物的杀菌效果并估计药物相互作用。

结果

与依从治疗相比,不依从治疗方案使治疗持续时间增加了近1.6倍和3.4倍。基于症状的间歇治疗是一种不依从形式,可能导致治疗失败以及耐药突变体的加速生长和演变,导致耐多药结核病出现的概率大幅提高至4.17×10(-3)(95%置信区间2.10×10(-4)-1.28×10(-2))。总体而言,最佳治疗方案的确定取决于不同类型的用药依从性。

结论

我们的模型不仅可以预测进化动态,还能量化治疗效果。更广泛地说,我们的模型为改进治疗方案和建立可用于预防耐药性的耐药出现阈值提供了一个定量框架。

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