Chevillotte Grégoire, Bernard Audrey, Varret Clémence, Ballet Pascal, Bodin Laurent, Roudot Alain-Claude
Laboratoire d'Evaluation du Risque Chimique pour le Consommateur (LERCCo), Université Européenne de Bretagne - Université de Bretagne Occidentale (UEB-UBO), UFR Sciences et Techniques, 6 Av. Victor Le Gorgeu, CS93837, 29238 Brest Cedex 3, France.
Laboratoire d'Evaluation du Risque Chimique pour le Consommateur (LERCCo), Université Européenne de Bretagne - Université de Bretagne Occidentale (UEB-UBO), UFR Sciences et Techniques, 6 Av. Victor Le Gorgeu, CS93837, 29238 Brest Cedex 3, France.
Food Chem Toxicol. 2017 Dec;110:214-228. doi: 10.1016/j.fct.2017.10.030. Epub 2017 Oct 21.
In a previous study, we presented a new method that uses a large-scale sampling system to probabilistically assess non-monotonic dose-response curves. The statistical plausibility of the characterization was governed by the probability of the dominant category, but gave no information about the specific robustness of the curve. In this paper we propose an improvement to the method by integrating a scoring system based on 4 criteria which can be used to assess the slope robustness of each of the 10,000 sampled curves. The distribution criterion which assesses the number of doses forming a slope, the intensity criterion which assesses the amplitude of the response, and the minimum and maximum confirmation criteria which increase the certainty that the response is present. The probabilistic method was tested on 294 dose-response curves taken from 2 databases and 2 other methodologies currently proposed. A total of 544 dose-response curves have been processed. The developed method offers a concrete and probabilistic characterization of the type of curve analyzed. It evaluates its statistical plausibility and its robustness according to its sampling curves. This method is applicable to all types of data (continuous and discrete) and all experimental curves starting from theoretically 3 doses at least.
在之前的一项研究中,我们提出了一种新方法,该方法使用大规模采样系统来概率性地评估非单调剂量反应曲线。特征描述的统计合理性由主导类别概率决定,但未提供有关曲线具体稳健性的信息。在本文中,我们通过整合基于4个标准的评分系统对该方法进行了改进,该评分系统可用于评估10000条采样曲线中每条曲线的斜率稳健性。分布标准评估形成斜率的剂量数量,强度标准评估反应幅度,最小和最大确认标准提高反应存在的确定性。概率方法在从2个数据库获取的294条剂量反应曲线以及目前提出的另外2种方法上进行了测试。总共处理了544条剂量反应曲线。所开发的方法对分析的曲线类型提供了具体的概率性特征描述。它根据采样曲线评估其统计合理性及其稳健性。该方法适用于所有类型的数据(连续和离散)以及所有至少从理论上3个剂量开始的实验曲线。