Kramer M S, Leventhal J M, Hutchinson T A, Feinstein A R
JAMA. 1979 Aug 17;242(7):623-32.
Despite widespread clinical and epidemiologic attention to adverse drug reactions (ADRs), their clinical identification has been a nonreproducible act of unspecified subjective judgment; adequate operational criteria have not been available for diagnostic decisions about the cause of an observed untoward clinical manifestation. To improve scientific precision in the diagnosis of ADRs, we have developed an algorithm that provides detailed operational criteria for ranking the probability of causation when ADR is suspected between a drug and a clinical manifestation. The algorithm provides a scoring system for six axes of decision strategy: previous general experience with the drug, alternative etiologic candidates, timing of events, drug levels and evidence of overdose, dechallenge, and rechallenge. The sum of the scores is ordinally partitioned to rate the candidate ADR as definite, probable, possible, or unlikely.
尽管临床和流行病学对药物不良反应（ADR）广泛关注，但其临床识别一直是一种不可重复的、主观判断不明确的行为；对于观察到的不良临床表现的病因诊断决策，尚无充分的操作标准。为提高药物不良反应诊断的科学准确性，我们开发了一种算法，该算法提供了详细的操作标准，用于在怀疑药物与临床表现之间存在药物不良反应时对因果关系的可能性进行排序。该算法为决策策略的六个轴提供了一个评分系统：药物既往总体经验、其他病因候选因素、事件发生时间、药物水平及过量证据、撤药反应和再激发反应。分数总和按顺序划分，以将候选药物不良反应评为肯定、很可能、可能或不太可能。
