4.4 Article

Estimating Efficacy and Drug ED50's Using von Frey Thresholds: Impact of Weber's Law and Log Transformation

期刊

JOURNAL OF PAIN
卷 13, 期 6, 页码 519-523

出版社

CHURCHILL LIVINGSTONE
DOI: 10.1016/j.jpain.2012.02.009

关键词

Pain; von Frey filament; paw withdrawal threshold; ED50

向作者/读者索取更多资源

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. (C) 2012 by the American Pain Society

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据