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吉非替尼的血药浓度-时间曲线下面积估算的有限采样策略。

A limited sampling strategy for estimation of the area under the plasma concentration-time curve of gefitinib.

出版信息

Ther Drug Monit. 2014 Feb;36(1):24-9. doi: 10.1097/FTD.0b013e31829dabbc.

Abstract

PURPOSE

The aim of this study was to develop a limited sampling strategy (LSS) to estimate the area under the concentration-time curve (AUC) of gefitinib using data from 18 patients with non-small-cell lung cancer.

METHODS

On day 14 after beginning daily therapy with 250 mg of gefitinib, plasma samples were collected just before (C(0h), 24 hours after the 13th administration) and 1, 2, 4, 6, 8, 12, and 24 hours (C(nh)) after gefitinib administration and were analyzed by high-performance liquid chromatography.

RESULTS

The predicted AUC from 0 to 24 hours (AUC₀₋₂₄) from the single time point of C(12h) showed the highest correlation with the measured AUC₀₋₂₄ of gefitinib (AUC₀₋₂₄ = 20.0 · C(12h) + 1348.0; r² = 0.9623; P , 0.0001). The 95% confidence intervals of the slopes and intercepts of the formulae obtained by bootstrap analysis indicated acceptable accuracy and robustness in the prediction of AUC₀₋₂₄ using C(0h), C(1h), C(12h), and C(1h) + C(12h). The median AUC₀₋₂₄ and C(0h) of gefitinib in patients with diarrhea (n = 8) were higher than those without diarrhea (n = 10) (15,043 versus 8918 ng·h·mL⁻¹, respectively, P = 0.0164 and 542 versus 261 ng/mL, respectively, P = 0.0263). The area under the receiver operator curve was 0.813, giving the best sensitivity (75%) and specificity (90%) at a C(0h) threshold of 398 ng/mL.

CONCLUSIONS

Use of the C(12h) single time point is recommended for the gefitinib AUC₀₋₂₄ predictive equation; however, total estimation of the AUC₀₋₂₄ of gefitinib at the single point of C(0h) was also precise. C(0h) monitoring of gefitinib might be beneficial during gefitinib therapy, because of a high variability in gefitinib exposure among patients taking 250 mg. Further examination of the correlation between clinical evaluation and the gefitinib exposure is necessary.

摘要

目的

本研究旨在开发一种有限采样策略(LSS),以使用 18 名非小细胞肺癌患者的数据估算吉非替尼的浓度-时间曲线下面积(AUC)。

方法

在开始每日 250mg 吉非替尼治疗的第 14 天,在给药后 1、2、4、6、8、12 和 24 小时(C(nh))以及给药前 24 小时(C(0h))采集血浆样本。采用高效液相色谱法进行分析。

结果

单次 C(12h)时间点预测的 AUC₀₋₂₄(AUC₀₋₂₄)与吉非替尼的实测 AUC₀₋₂₄(AUC₀₋₂₄)相关性最高(AUC₀₋₂₄=20.0·C(12h)+1348.0;r²=0.9623;P<0.0001)。通过 bootstrap 分析得到的公式斜率和截距的 95%置信区间表明,使用 C(0h)、C(1h)、C(12h)和 C(1h)+C(12h)预测 AUC₀₋₂₄时,预测值具有较好的准确性和稳健性。腹泻(n=8)患者的吉非替尼 AUC₀₋₂₄和 C(0h)中位数均高于无腹泻(n=10)患者(分别为 15043 与 8918ng·h·mL⁻¹,P=0.0164 和 542 与 261ng/mL,P=0.0263)。受试者工作特征曲线下面积为 0.813,C(0h)阈值为 398ng/mL 时,预测的 AUC₀₋₂₄具有最佳的灵敏度(75%)和特异性(90%)。

结论

建议使用 C(12h)单点时间点来估算吉非替尼 AUC₀₋₂₄的预测方程,但单点 C(0h)也能准确估算吉非替尼 AUC₀₋₂₄的总估计值。由于服用 250mg 吉非替尼的患者之间吉非替尼暴露量的变异性很大,因此在吉非替尼治疗期间监测 C(0h)可能会有所帮助。需要进一步检查临床评估与吉非替尼暴露量之间的相关性。

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