首页> 外文期刊>Therapeutic Drug Monitoring >Validation of sparse sampling strategies to estimate cyclosporine A area under the concentration-time curve using either a specific radioimmunoassay or high-performance liquid chromatography method.
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Validation of sparse sampling strategies to estimate cyclosporine A area under the concentration-time curve using either a specific radioimmunoassay or high-performance liquid chromatography method.

机译:使用特定的放射免疫分析法或高效液相色谱法验证了在浓度-时间曲线下估算环孢菌素A面积的稀疏采样策略。

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INTRODUCTION: Area under the concentration-time curve (AUC) has been advocated as a better parameter to monitor cyclosporine A than trough concentrations. Up to now, more than 100 equations to estimate AUC using a limited sampling strategy have been published, but not all have been validated. MATERIAL AND METHODS: Eight equations for AUC0-12h and two for AUC0-8h were validated. Concentrations of cyclosporine A were analyzed by high-performance liquid chromatography (HPLC) and a specific radioimmunoassay (RIA) method. Forty male renal transplant patients were included in the study. Blood samples were taken predose and at 0.5, 1, 1.5, 2, 3, 5, 8, and 12 hours after the morning dose when the patient was in steady state. The percentage prediction error (%pe) was used for an assessment of the performance of the equations. Mean %pe less than +/- 15% and absolute %pe less than 30% in 95% of predictions were considered to be acceptable. Other possibilities such as %pe less than 25%, 20%, and 15% were also tested. RESULTS: Eight equations for AUC0-12h met the requirements using both assays, six in the HPLC set only and four in the RIA set only. The highest precision was obtained with AUC0-12h = 123.792 + 1.165*C1h + 3.021*C3h + 7.33*C8h proposed by de Mattos et al. The mean %pe was 1% +/- 8% (-16 to 19) for HPLC (values given as mean +/- standard deviation [range]) and -1 +/- 5 (-17 to 10) for RIA. Mean absolute %pe was 7 +/- 5 (0.0 to 19) for HPLC and 4 +/- 4 (0.0 to 17) for RIA. For clinical use, the most suitable equation was AUC0-12h = 363.078 + 8.77*C1h + 3.07*C3h proposed by Wacke et al, which produced the second lowest %pe and used two sampling points in the period of 1 to 3 hours after dose. The mean %pe was -7 +/- 10 (-25 to 25) for HPLC and 2.3 +/- 6 (-10 to 17) for RIA. Mean absolute %pe was 10 +/- 7 (0.4 to 25) for HPLC and 5 +/- 4 (0.0 to 17) for RIA. The equation: AUC0-8h = 55.37 + 2.89*C0h + 1.08*C1h0.9*C2h + 2.23*C3h proposed by Foradori et al met the criteria with 95% of prediction with absolute %pe less than 15% in the HPLC set and 10% in the RIA set. CONCLUSION: The validation of equations is of major importance for prediction precision, whereas the analytical method for limited sampling strategy proposals had no influence. Because of the wide interassay variability, it is also important to know which analytical method was used for AUC calculation when interpreting the results.
机译:引言:浓度-时间曲线下的面积(AUC)被认为是监测环孢菌素A的一个比槽浓度更好的参数。到目前为止,已经发布了100多种使用有限采样策略估算AUC的方程式,但尚未全部验证。材料与方法:验证了AUC0-12h的八个方程和AUC0-8h的两个方程。通过高效液相色谱(HPLC)和特异性放射免疫分析(RIA)方法分析环孢菌素A的浓度。该研究包括40名男性肾移植患者。当患者处于稳定状态时,在早晨剂量之后的0.5、1、1.5、2、3、5、8和12小时,在服药前和采血时​​采血。百分比预测误差(%pe)用于评估方程的性能。在95%的预测中,平均%pe小于+/- 15%和绝对%pe小于30%被认为是可以接受的。还测试了其他可能性,例如%pe小于25%,20%和15%。结果:两种测定法均满足八个AUC0-12h方程,仅在HPLC中设置了六个方程式,在RIA中仅设置了四个方程式。由de Mattos等人提出的AUC0-12h = 123.792 + 1.165 * C1h + 3.021 * C3h + 7.33 * C8h获得了最高的精度。 HPLC的平均%pe为1%+/- 8%(-16至19)(值以平均值+/-标准偏差[范围]给出),RIA的平均%pe为-1 +/- 5(-17至10)。 HPLC的平均绝对%pe为7 +/- 5(0.0到19),RIA的平均绝对%pe为4 +/- 4(0.0到17)。对于临床使用,最合适的公式是Wacke等人提出的AUC0-12h = 363.078 + 8.77 * C1h + 3.07 * C3h,该公式产生的PE值最低,在给药后1至3小时内使用了两个采样点。 HPLC的平均%pe为-7 +/- 10(-25至25),RIA的平均%pe为2.3 +/- 6(-10至17)。 HPLC的平均绝对%pe为10 +/- 7(0.4至25),RIA的平均绝对%pe为5 +/- 4(0.0至17)。 Foradori等人提出的等式:AUC0-8h = 55.37 + 2.89 * C0h + 1.08 * C1h0.9 * C2h + 2.23 * C3h符合以下标准:在HPLC组合中,预测的95%的绝对%pe小于15%,并且RIA设定中的10%。结论:方程的验证对于预测精度至关重要,而有限采样策略建议的分析方法则没有影响。由于批间差异很大,因此在解释结果时了解哪种分析方法用于AUC计算也很重要。

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