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Therapeutic mycophenolic Acid monitoring by means of limited sampling strategy in orthotopic heart transplant patients.

机译:通过有限采样策略对原位心脏移植患者进行治疗性麦考酚酸监测。

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Therapeutic drug monitoring (TDM) is essential to maintain the efficacy of many immunosuppressant drugs while minimizing their toxicity. TDM of mycophenolate mofetil requires area under the curve AUC determinations but appears laborious, costly, and clinically impractical. To overcome these problems, limited sampling strategies (LSS) have been proposed in adult and pediatric renal transplant patients. The purpose of this study was to develop an LSS in heart transplant patients. Forty-four mycophenolic acid (MPA) full AUC(0-12h) profiles were generated by high-performance liquid chromatography in nine heart transplant patients during the first 12 weeks posttransplant. Each patient received concomitant cyclosporine and prednisone therapy. Multiple stepwise regression analysis was used to define the time points of MPA levels to explain the MPA AUC(0-12h). Agreement between abbreviated AUC and the full AUC(0-12h) was tested by means of a Bland and Altman analysis. The highest coefficient of determination r(2) among MPA AUC and single concentrations (r(2) = .610) was observed with C(2), while C(12) provided the lowest one (r(2) = .003). Stepwise linear regression showed that the minimal model with the best estimation of MPA AUC(0-12h) was obtained at timed values of 1.25, 2, and 6 hours. The corresponding estimated model was AUC = 5.568 + 0.902 * C(1.25) + 2.022 * C(2) + 4.594 * C(6) (r(2) = .926). Bland and Altman analysis revealed good agreement between predicted AUC and full AUC. A further interesting model equation obtained by four samples was AUC = 3.800 + 1.015 * C(1.25) + 1.819 * C(2) + 1.566 * C(4) + 3.479 * C(6) (r(2) = .948).
机译:治疗药物监测(TDM)对于维持许多免疫抑制剂药物的功效同时最小化其毒性至关重要。霉酚酸酯的TDM需要曲线AUC测定下的面积,但显得费力,昂贵且在临床上不切实际。为了克服这些问题,已经提出了在成年和小儿肾移植患者中的有限采样策略(LSS)。这项研究的目的是为心脏移植患者开发LSS。在移植后的前12周内,通过高效液相色谱法在9位心脏移植患者中产生了44个麦考酚酸(MPA)完整AUC(0-12h)图。每例患者均接受环孢素和泼尼松治疗。使用多元逐步回归分析来定义MPA水平的时间点,以解释MPA AUC(0-12h)。通过Bland和Altman分析测试了缩写AUC与完整AUC(0-12h)之间的一致性。用C(2)观察到MPA AUC和单一浓度(r(2)= .610)中最高的测定系数r(2),而C(12)提供最低的测定系数(r(2)= .003) 。逐步线性回归表明,在1.25、2和6小时的计时值下获得了MPA AUC(0-12h)最佳估计的最小模型。相应的估计模型为AUC = 5.568 + 0.902 * C(1.25)+ 2.022 * C(2)+ 4.594 * C(6)(r(2)= .926)。布兰德(Bland)和奥特曼(Altman)分析显示,预测的AUC与完整AUC之间具有良好的一致性。由四个样本获得的另一个有趣的模型方程是AUC = 3.800 + 1.015 * C(1.25)+ 1.819 * C(2)+ 1.566 * C(4)+ 3.479 * C(6)(r(2)= .948) 。

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