Louik C, Lacouture P G, Mitchell A A, Kauffman R, Lovejoy F H, Yaffe S J, Shapiro S
Clin Pharmacol Ther. 1985 Aug;38(2):183-7. doi: 10.1038/clpt.1985.156.
To improve agreement among observers, several investigators have recently proposed methods (algorithms) to standardize assessments of causality for presumed adverse drug reactions. We evaluated one such method in the context of an intensive pediatric drug surveillance program. Four observers rated 50 randomly selected case reports drawn from the program, first using only general guidelines and then, several months later, using the strict criteria of the algorithm. Agreement among observers was poor in both study phases. The presence of selected characteristics of adverse events (e.g., major severity) did not improve agreement in either phase of the study. We conclude that routine use of such algorithms in drug surveillance programs is not likely to be of benefit.
为提高观察者之间的一致性,最近几位研究人员提出了一些方法(算法),以规范对疑似药物不良反应因果关系的评估。我们在一项密集的儿科药物监测计划中评估了其中一种方法。四名观察者对从该计划中随机抽取的50份病例报告进行评分,首先仅使用一般指南,几个月后,再使用该算法的严格标准。在两个研究阶段,观察者之间的一致性都很差。不良事件的特定特征(例如,严重程度)的存在在研究的任何阶段都没有提高一致性。我们得出结论,在药物监测计划中常规使用此类算法不太可能有益。