Estimating Efficacy and Drug ED50's Using von Frey Thresholds: Impact of Weber's Law and Log Transformation
- 作者：Charles Mills ; charles.mills@abbott.com ; David LeBlond ; Shailen Joshi ; Chang Zhu ; Gin Hsieh ; Peer Jacobson ; Michael Meyer ; Michael Decker
- 关键词：Pain ; von Frey filament ; paw withdrawal threshold ; ED50
- 刊名：The Journal of Pain
- 出版年：2012
- 期刊代码：332_15265900
- 类别：med
- 出版时间：June, 2012
- 卷：13
- 期：6
- 页码：519-523
- 文件大小：408 K
摘要
The use of von Frey filaments, originally developed by Maximilian von Frey, has become the cornerstone for assaying mechanical sensitivity in animal models and is widely used for human assessment. While there are certain limitations associated with their use that make comparisons between studies not straightforward at times, such as stimulus duration and testing frequency, von Frey filaments provide a good measurement of mechanosensation. Here we describe the application of von Frey filaments to testing in animal models, specifically with respect to determining changes in sensory thresholds in a pain state using the Dixon up-down method. In a literature survey, we found that up to 75%of reports using this method analyze the data with parametric statistical analysis and of those that used nonparametric analysis, none took into account that mechanical sensation is perceived on a logarithmic scale (Weber's Law) when calculating efficacy. Here we outline a more rigorous analysis for calculating efficacy and ED50's from von Frey data that incorporates Weber's Law. We show that this analysis makes statistical and biological sense and provide a specific example of how this change affects data analysis that brings results from animal models more in line with clinical observations.
Perspective
This focus article argues that analyzing von Frey paw withdrawal threshold data obtained by using the Dixon up-down method without considering Weber's Law is inappropriate. An analysis method that incorporates how mechanical sensation is perceived and how its application brings results from animal models more in line with clinical data is presented.