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一种用于大规模临床试验中不良事件分类的算法。

An algorithm for the classification of untoward events in large scale clinical trials.

作者信息

Emanueli A, Sacchetti G

出版信息

Agents Actions Suppl. 1980;7:318-22.

PMID:6941682
Abstract

The algorithm described in this paper derives from a proposal by Karch and Lasagna and was developed for analysis of events reported in large scale clinical trials. It is presented in the form of a decision table which allows classification of events on a five-point scale according to the probability of their relationship with the drug under study. The degree of reproducibility of judgements made with the algorithm has been assessed and the decision table has been utilized for classifying all untoward events reported during an extended clinical trial with an anti-inflammatory drug.

摘要

本文所述的算法源自卡奇(Karch)和拉萨尼亚(Lasagna)的一项提议,是为分析大规模临床试验中报告的事件而开发的。它以决策表的形式呈现,该决策表允许根据事件与所研究药物的关联概率,将事件分为五个等级。已经评估了使用该算法进行判断的可重复性程度,并且该决策表已用于对一种抗炎药物的延长临床试验期间报告的所有不良事件进行分类。

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