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利用结核分枝杆菌单核苷酸多态性预测氟喹诺酮类药物治疗反应。

Using Mycobacterium tuberculosis Single-Nucleotide Polymorphisms To Predict Fluoroquinolone Treatment Response.

机构信息

Department of Medicine, University of California San Diego, La Jolla, California, USA

Department of Pediatrics, University of California San Diego, La Jolla, California, USA.

出版信息

Antimicrob Agents Chemother. 2019 Jun 24;63(7). doi: 10.1128/AAC.00076-19. Print 2019 Jul.

Abstract

Clinical phenotypic fluoroquinolone susceptibility testing of is currently based on growth at a single critical concentration, which provides limited information for a nuanced clinical response. We propose using specific resistance-conferring mutations in together with population pharmacokinetic and pharmacodynamic modeling as a novel tool to better inform fluoroquinolone treatment decisions. We sequenced the resistance-determining region of 138 clinical isolates collected from India, Moldova, Philippines, and South Africa and then determined each strain's MIC against ofloxacin, moxifloxacin, levofloxacin, and gatifloxacin. Strains with specific single-nucleotide polymorphisms (SNPs) were grouped into high or low drug-specific resistance categories based on their empirically measured MICs. Published population pharmacokinetic models were then used to explore the pharmacokinetics and pharmacodynamics of each fluoroquinolone relative to the empirical MIC distribution for each resistance category to make predictions about the likelihood of patients achieving defined therapeutic targets. In patients infected with isolates containing SNPs associated with a fluoroquinolone-specific low-level increase in MIC, models suggest increased fluoroquinolone dosing improved the probability of achieving therapeutic targets for gatifloxacin and moxifloxacin but not for levofloxacin and ofloxacin. In contrast, among patients with isolates harboring SNPs associated with a high-level increase in MIC, increased dosing of levofloxacin, moxifloxacin, gatifloxacin, or ofloxacin did not meaningfully improve the probability of therapeutic target attainment. We demonstrated that quantifiable fluoroquinolone drug resistance phenotypes could be predicted from rapidly detectable SNPs and used to support dosing decisions based on the likelihood of patients reaching therapeutic targets. Our findings provide further supporting evidence for the moxifloxacin clinical breakpoint recently established by the World Health Organization.

摘要

目前,临床表型氟喹诺酮药敏试验基于单一临界浓度下的 生长情况,这为细致的临床反应提供了有限的信息。我们提出使用 中特定的耐药相关突变,结合群体药代动力学和药效动力学模型,作为一种更好地为氟喹诺酮治疗决策提供信息的新工具。我们对从印度、摩尔多瓦、菲律宾和南非收集的 138 株临床 分离株的 耐药决定区进行了测序,然后测定了每种菌株对氧氟沙星、莫西沙星、左氧氟沙星和加替沙星的 MIC。根据经验测量的 MIC,将具有特定 单核苷酸多态性 (SNP) 的菌株分为高或低药物特异性耐药类别。然后,使用已发表的群体药代动力学模型来探索每种氟喹诺酮相对于每个耐药类别的经验 MIC 分布的药代动力学和药效动力学,以预测患者达到既定治疗目标的可能性。在感染含有与氟喹诺酮特异性 MIC 轻度升高相关的 SNP 的 分离株的患者中,模型表明增加氟喹诺酮剂量可提高达到加替沙星和莫西沙星治疗目标的可能性,但不能提高达到左氧氟沙星和氧氟沙星治疗目标的可能性。相比之下,在携带与 MIC 大幅升高相关 SNP 的分离株感染患者中,增加左氧氟沙星、莫西沙星、加替沙星或氧氟沙星的剂量并不能显著提高达到治疗目标的可能性。我们证明,可从快速检测到的 SNP 预测可量化的氟喹诺酮药物耐药表型,并根据患者达到治疗目标的可能性支持剂量决策。我们的研究结果为世界卫生组织最近确立的莫西沙星临床折点提供了进一步的支持证据。

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