Tembo A V, Schork M A, Wagner J G
Steroids. 1976 Sep;28(3):387-403. doi: 10.1016/0039-128x(76)90048-9.
An extensive survey of radioimmunoassay calibration data for prednisolone, prednisone and digoxin indicated that the common practice of preparing calibration curves with individual subject's pre-dose plasma or serum, and using this to estimate unknown concentrations for the same subject, is not supported by statistical considerations. Preparation of calibration plots from pooled data is better because this introduces less bias in estimated concentrations. Such a method also saves a great deal of time, since it is not necessary to repeat the calibration procedure each time, "unknowns" are being assayed. The data suggest that there is no optimum calibration plot for all radioimmunoassays. Rather, each antibody-drug combination should be investigated thoroughly to determine the best calibration plot for the particular combination. We found that the best calibration plots are: the logistic-logarithmic plot for prednisolone; nonlinear least squares fit to a polyexponential equation for nisolone; nonlinear least squares fit to a polyexponential equation for prednisone; and a weighted least squares regression of normalized % bound versus concentration for figoxin. The error in the radioimmunoassay is usually concentration-dependent, and, in certain regions of the standard curve, is larger than the literature indicates, since, frequently, the error has been gauged from % bound values, but should be guaged from inversely-estimated concentrations.
一项针对泼尼松龙、泼尼松和地高辛放射免疫分析校准数据的广泛调查表明，用个体受试者给药前的血浆或血清制备校准曲线，并以此来估计同一受试者未知浓度的常见做法，从统计学角度来看是没有依据的。用合并数据制备校准图更好，因为这样在估计浓度时引入的偏差更小。这种方法还能节省大量时间，因为每次检测“未知样本”时无需重复校准程序。数据表明，并非所有放射免疫分析都存在最佳校准图。相反，对于每一种抗体 - 药物组合，都应进行全面研究，以确定该特定组合的最佳校准图。我们发现最佳校准图如下：泼尼松龙采用逻辑对数图；尼索龙采用非线性最小二乘法拟合多指数方程；泼尼松采用非线性最小二乘法拟合多指数方程；地高辛采用归一化结合百分比与浓度的加权最小二乘回归。放射免疫分析中的误差通常与浓度相关，并且在标准曲线的某些区域，误差比文献表明的要大，因为误差通常是根据结合百分比值来衡量的，但应该根据反推估计的浓度来衡量。
