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Models for the prediction of mycophenolic acid area under the curve using a limited-sampling strategy and an enzyme multiplied immunoassay technique in Chinese patients undergoing liver transplantation

机译:应用有限采样策略和酶联免疫测定技术预测中国肝移植患者曲线下霉酚酸面积的模型

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BACKGROUND: An enzyme multiplied immunoassay technique (EMIT) provides convenient and accurate measurements of mycophenolic acid (MPA) concentrations for determination of immunosuppression during treatment with mycophenolate mofetil (MMF). No abbreviated model for estimating the full 12-hour MPA AUC using an EMIT assay in liver transplant recipients has been described previously. OBJECTIVE: This study was conducted to determine the best model for predicting the MPA AUC using the EMIT method and a limited-sampling strategy in Chinese patients undergoing liver transplantation. METHODS: The study enrolled consecutive liver transplant patients who were receiving MMF 1 g BID along with tacrolimus. A complete MPA pharmacokinetic profile was obtained for each patient on a single day, 7 to 14 days after transplantation. The EMIT method was used to determine MPA concentrations before dosing and at 0.5, 1, 1.5, 2, 4, 6, 8, 10, and 12 hours after dosing on the sampling day. Multiple linear regression analysis wasused to evaluate potential models for estimating the full 12-hour MPA AUC. The accuracy and robustness of the models were evaluated using bootstrap analysis. Prediction error and prediction bias were calculated. Agreement between the estimated MPA AUC(0-12) and the full 12-hour MPA AUC was investigated using Bland-Altman analysis. RESULTS: The study enrolled 48 Chinese liver transplant recipients (45 male, 3 female) with a mean (SD) age of 50 (12) years, mean weight of 64 (12) kg, and mean height of 169 (6) cm. Twenty-four models that included blood sampling at 1 through 4 time points were developed (r(2) = 0.015-0.950). Four models with the highest r(2) values were selected; the lack of significant differences from the original dataset on bootstrap analysis indicated acceptable accuracy and robustness. The best model for predicting the MPA AUC(0-12) employed concentrations at 1, 2, 4, and 8 hours; 40 of 48 (83.3%) MPA AUC(0-12) values estimated using this model were within 15% of the full 12-hour MPA AUC. This model had a minimal mean prediction error (mean [SD], 0.27% [1.79%]) and mean absolute prediction error (8.83% [1.24%]). On Bland-Altman analysis, this model also had the best agreement between the estimated MAP AUC(0-12) and the full 12-hour MPA AUC, with a mean error of 9.02 mg . h/L. CONCLUSIONS: In this small group of Chinese liver transplant patients receiving MMF and concomitant tacrolimus, models for estimating the MPA AUC(0-12) were developed using the EMIT method and a limited-sampling strategy. The best model for prediction of the full 12-hour MPA AUC was 4.46 + 0.81 . C1 + 1.78 . C(2)+2.51.C(4)+4.94.C8.
机译:背景:酶联免疫测定技术(EMIT)为霉酚酸酯(MMF)治疗期间的霉菌酚酸(MPA)浓度提供了方便,准确的测量方法,用于确定免疫抑制作用。以前没有描述过使用EMIT测定法在肝移植受者中估算完整的12小时MPA AUC的简化模型。目的:本研究旨在确定使用EMIT方法和有限采样策略对中国肝移植患者进行MPA AUC预测的最佳模型。方法:该研究招募了接受MMF 1 g BID和他克莫司治疗的连续肝移植患者。移植后7到14天,每天在每位患者上获得完整的MPA药代动力学概况。 EMIT方法用于确定给药前和采样日给药后0.5、1、1.5、2、4、6、8、10和12小时的MPA浓度。使用多元线性回归分析来评估潜在模型,以估算完整的12小时MPA AUC。使用引导分析评估模型的准确性和鲁棒性。计算了预测误差和预测偏差。使用Bland-Altman分析研究了估计的MPA AUC(0-12)与完整的12小时MPA AUC之间的一致性。结果:该研究招募了48位中国肝移植受者(男性45位,女性3位),平均(SD)年龄为50(12)岁,平均体重为64(12)kg,平均身高为169(6)cm。开发了包括1至4个时间点的血液采样的二十四个模型(r(2)= 0.015-0.950)。选择了具有最高r(2)值的四个模型;自举分析与原始数据集之间没有显着差异,表明可接受的准确性和鲁棒性。预测MPA AUC(0-12)的最佳模型采用的浓度分别为1、2、4和8小时。使用此模型估算的48个MPA AUC(0-12)值中有40个(83.3%)在整个12小时MPA AUC的15%之内。该模型具有最小的平均预测误差(平均值[SD],0.27%[1.79%])和平均的绝对预测误差(8.83%[1.24%])。在Bland-Altman分析中,该模型在估计的MAP AUC(0-12)和完整的12小时MPA AUC之间也具有最佳一致性,平均误差为9.02 mg。 h / L。结论:在这小部分接受MMF和他克莫司治疗的中国肝移植患者中,使用EMIT方法和有限采样策略开发了MPA AUC(0-12)估算模型。预测整个12小时MPA AUC的最佳模型是4.46 + 0.81。 C1 + 1.78。 C(2)+ 2.51.C(4)+ 4.94.C8。

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