McCauley D L, Lum B L, Sikic B I
State University of New York at Stony Brook 11794, USA.
Cancer Chemother Pharmacol. 1996;37(3):286-8. doi: 10.1007/BF00688330.
Different methods to calculate interval area under the curve (AUC) data may produce substantial error. The purpose of this study was to compare methods of calculating etoposide AUC and determine the effect of these values on white blood cell (WBC) count nadir predictions calculated from a previously reported equation. Three AUC calculation methods were used: (1) the linear trapezoidal method, (2) a combination of the linear and logarithmic trapezoidal methods, and (3) the Lagrange method. Since none of the methods for determining the AUC could be considered the standard, the methods were evaluated by comparing differences between pairs of calculated AUC values by each method. The 95% CI for differences between all pairs of AUC values were greater than zero (no difference) indicating significance. Consistent with the smoother fitting function between data points, the Lagrange method tended to produce a larger AUC, lower clearance values, and lower WBC nadir count predictions than the other methods. The largest difference encountered was between the Lagrange and the linear-log AUC methods with a mean value of 16.9 micrograms h/ml (95% CI 9.4-24.3) This difference would account for approximately 11% of the total AUC. Using a previously published equation, where WBC nadir = -0.057 +0.048 x etoposide clearance, with clearance determined as dose/AUC, mean differences in calculated WBC nadir count values between the three AUC methods ranged from 80 to 220 cells/microliters, which would be expected to be of little clinical consequence. The precision of this equation, using data derived from linear trapezoidal AUC calculations, had a mean absolute error of 0.93 x 10(3)/microliters (95% CI 0.53-1.32). Our findings suggest that any of the three mathematical methods studied would produce similar etoposide AUC values and pharmacodynamic predictions. Further, these findings also suggest that the major limitation in predicting etoposide leukopenia lies with the imprecision of the pharmacodynamic model more so than the ability to accurately determine the AUC. However, our findings may not be applicable if other factors intervene which dramatically alter the shape of the etoposide concentration-time curve.
计算曲线下面积(AUC)数据区间的不同方法可能会产生显著误差。本研究的目的是比较依托泊苷AUC的计算方法,并确定这些值对根据先前报道的方程计算的白细胞(WBC)计数最低点预测值的影响。使用了三种AUC计算方法:(1)线性梯形法,(2)线性和对数梯形法的组合,以及(3)拉格朗日法。由于确定AUC的方法均不能被视为标准方法,因此通过比较每种方法计算的AUC值对之间的差异来评估这些方法。所有AUC值对之间差异的95%置信区间大于零(无差异),表明具有显著性。与数据点之间更平滑的拟合函数一致,拉格朗日法往往比其他方法产生更大的AUC、更低的清除率值和更低的WBC最低点计数预测值。遇到的最大差异是拉格朗日法与线性-对数AUC法之间的差异,平均值为16.9微克·小时/毫升(95%置信区间9.4 - 24.3)。这种差异约占总AUC的11%。使用先前发表的方程,其中WBC最低点=-0.057 + 0.048×依托泊苷清除率,清除率定义为剂量/AUC,三种AUC方法之间计算的WBC最低点计数值的平均差异范围为80至220个细胞/微升,预计这在临床上几乎没有影响。使用从线性梯形AUC计算得出的数据,该方程的精度平均绝对误差为0.93×10³/微升(95%置信区间0.53 - 1.32)。我们的研究结果表明,所研究的三种数学方法中的任何一种都会产生相似的依托泊苷AUC值和药效学预测。此外,这些研究结果还表明,预测依托泊苷引起的白细胞减少的主要限制在于药效学模型的不精确性,而不是准确确定AUC的能力。然而,如果其他因素介入并显著改变依托泊苷浓度-时间曲线的形状,我们的研究结果可能不适用。