Meddings J B, Scott R B, Fick G H
Department of Medicine, University of Calgary, Alberta, Canada.
Am J Physiol. 1989 Dec;257(6 Pt 1):G982-9. doi: 10.1152/ajpgi.1989.257.6.G982.
A number of physiological or pharmacological studies generate sigmoidal dose-response curves. Ideally, data analysis should provide numerical solutions for curve parameters. In addition, for curves obtained under different experimental conditions, testing for significant differences should be easily performed. We have reviewed the literature over the past 3 years in six journals publishing papers in the field of gastrointestinal physiology and established the curve analysis technique used in each. Using simulated experimental data of known error structure, we have compared these techniques with nonlinear regression analysis. In terms of their ability to provide accurate estimates of ED50 and maximal response, none approached the accuracy and precision of nonlinear regression. This technique is as easily performed as the classic methods and additionally provides an opportunity for rigorous statistical analysis of data. We present a method of determining the significance of differences found in the ED50 and maximal response under different experimental conditions. The method is versatile and applicable to a variety of different physiological and pharmacological dose-response curves.
许多生理学或药理学研究都会生成S形剂量反应曲线。理想情况下,数据分析应能为曲线参数提供数值解。此外,对于在不同实验条件下获得的曲线,应能轻松进行显著性差异检验。我们回顾了过去3年在六本发表胃肠生理学领域论文的期刊上的文献,并确定了每本期刊所使用的曲线分析技术。利用已知误差结构的模拟实验数据,我们将这些技术与非线性回归分析进行了比较。就提供ED50和最大反应的准确估计的能力而言,没有一种方法能达到非线性回归的准确性和精确性。该技术与经典方法一样易于实施,此外还为数据的严格统计分析提供了机会。我们提出了一种确定在不同实验条件下ED50和最大反应中发现的差异的显著性的方法。该方法具有通用性,适用于各种不同的生理学和药理学剂量反应曲线。