Albany College of Pharmacy and Health Sciences, 106 New Scotland Avenue, Albany, NY 12208, USA.
Antimicrob Agents Chemother. 2011 Sep;55(9):4277-82. doi: 10.1128/AAC.01674-10. Epub 2011 Jun 13.
While current data indicate only free (unbound) drug is pharmacologically active and is most predictive of response, pharmacodynamic studies of vancomycin have been limited to measurement of total concentrations. The protein binding of vancomycin is thought to be approximately 50%, but considerable variability surrounds this estimate. The present study sought to determine the extent of vancomycin protein binding, to identify factors that modulate its binding, and to create and validate a prediction tool to estimate the extent of protein binding based on individual clinical factors. This single-site prospective cohort study included hospitalized adult patients treated with vancomycin and with a vancomycin serum concentration determination available. Linear regression was used to predict the free vancomycin concentration (f[vanco]) and to determine the clinical factors modulating vancomycin protein binding. Among the 50 patients in the study, the mean protein binding was 41.5%. The strongest predictor of f[vanco] was the total vancomycin concentration (total [vanco]), and this was modified by dialysis and total protein of ≥6.7 g/dl as covariates. The algebraic expression from the final prediction model was f[vanco] = 0.643 + 0.560 × total [vanco] - {0.067 × total [vanco] × D} - {0.071 × total [vanco] × TP} where D = 1 if dialysis dependent or 0 if not dialysis dependent, and TP = 1 if total protein is ≥6.7 g/dl or 0 if total protein is <6.7 g/dl. The R(2) of the final prediction model was 0.959 (P < 0.001). Validation of our model was performed in 13 patients, and the predictive performance was highly favorable (R(2) was 0.9, and bias and precision were 0.18 and 0.18, respectively). Prediction models such as ours can be utilized in future pharmacokinetics and pharmacodynamics studies evaluating the exposure-response profile and to determine the pharmacodynamic target of interest as it relates to the free concentration.
虽然目前的数据表明只有游离（未结合）药物在药理学上具有活性，并且最能预测反应，但万古霉素的药效动力学研究仅限于总浓度的测量。万古霉素的蛋白结合被认为约为 50%，但这个估计值存在很大的变异性。本研究旨在确定万古霉素蛋白结合的程度，确定调节其结合的因素，并创建和验证一个预测工具，根据个体临床因素估计蛋白结合的程度。这项单站点前瞻性队列研究包括接受万古霉素治疗且有万古霉素血清浓度测定值的住院成年患者。线性回归用于预测游离万古霉素浓度（f[vanco]），并确定调节万古霉素蛋白结合的临床因素。在研究的 50 名患者中，平均蛋白结合率为 41.5%。f[vanco]的最强预测因子是总万古霉素浓度（总[vanco]），这一预测因子被透析和总蛋白≥6.7g/dl 作为协变量所修饰。最终预测模型的代数表达式为 f[vanco] = 0.643 + 0.560×总[vanco]-{0.067×总[vanco]×D}-{0.071×总[vanco]×TP}，其中 D=1 表示依赖透析，D=0 表示不依赖透析，TP=1 表示总蛋白≥6.7g/dl，TP=0 表示总蛋白<6.7g/dl。最终预测模型的 R(2)为 0.959（P<0.001）。在 13 名患者中进行了我们模型的验证，预测性能非常优异（R(2)为 0.9，偏差和精度分别为 0.18 和 0.18）。像我们这样的预测模型可以在未来的药代动力学和药效动力学研究中用于评估暴露-反应曲线，并确定与游离浓度相关的感兴趣的药效学目标。
