Serum Drug Concentrations Predictive of Pulmonary Tuberculosis Outcomes
Serum Drug Concentrations Predictive of Pulmonary Tuberculosis Outcomes
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DOI：
10.1093/infdis/jit352
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发表时间：
2013-11-01
影响因子：
6.4
通讯作者：
Gumbo, Tawanda
中科院分区：
文献类型：
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作者：
Pasipanodya, Jotam G.;McIlleron, Helen;Gumbo, Tawanda
背景。基于结核病的中空纤维系统模型，我们假设微生物学失败和获得性耐药性主要是由药代动力学变异性导致的低药物浓度驱动的。方法。前瞻性地收集了南非西开普省 142 名结核病患者的临床和药代动力学数据。确定了每位患者异烟肼、利福平和吡嗪酰胺的药代动力学参数。然后对患者进行长达 2 年的随访。分类和回归树分析用于识别和排序不良长期结果的临床预测因子，例如微生物学失败或死亡或复发。结果。患者之间的药物浓度和药代动力学差异很大。 35 名 (25%) 患者的长期结果不佳。按重要性排序，长期结果不佳的 3 个最重要预测因子是吡嗪酰胺 24 小时浓度-时间曲线下面积 (AUC)
Background. Based on a hollow-fiber system model of tuberculosis, we hypothesize that microbiologic failure and acquired drug resistance are primarily driven by low drug concentrations that result from pharmacokinetic variability.Methods. Clinical and pharmacokinetic data were prospectively collected from 142 tuberculosis patients in Western Cape, South Africa. Compartmental pharmacokinetic parameters of isoniazid, rifampin, and pyrazinamide were identified for each patient. Patients were then followed for up to 2 years. Classification and regression tree analysis was used to identify and rank clinical predictors of poor long-term outcome such as microbiologic failure or death, or relapse.Results. Drug concentrations and pharmacokinetics varied widely between patients. Poor long-term outcomes were encountered in 35 (25%) patients. The 3 top predictors of poor long-term outcome, by rank of importance, were a pyrazinamide 24-hour area under the concentration-time curve (AUC)