A statistical methodology for drug–drug interaction surveillance

药品 药物与药物的相互作用 成对比较 计算机科学 药物不良反应 逻辑回归 医学 药物反应 药物相互作用 上市后监督 数据挖掘 药理学 不利影响 内科学 人工智能
作者
G. Niklas Norén,Rolf Sundberg,Andrew Bate,I. Ralph Edwards
出处
期刊:Statistics in Medicine [Wiley]
卷期号:27 (16): 3057-3070 被引量:194
标识
DOI:10.1002/sim.3247
摘要

Interaction between drug substances may yield excessive risk of adverse drug reactions (ADRs) when two drugs are taken in combination. Collections of individual case safety reports (ICSRs) related to suspected ADR incidents in clinical practice have proven to be very useful in post-marketing surveillance for pairwise drug--ADR associations, but have yet to reach their full potential for drug-drug interaction surveillance. In this paper, we implement and evaluate a shrinkage observed-to-expected ratio for exploratory analysis of suspected drug-drug interaction in ICSR data, based on comparison with an additive risk model. We argue that the limited success of previously proposed methods for drug-drug interaction detection based on ICSR data may be due to an underlying assumption that the absence of interaction is equivalent to having multiplicative risk factors. We provide empirical examples of established drug-drug interaction highlighted with our proposed approach that go undetected with logistic regression. A database wide screen for suspected drug-drug interaction in the entire WHO database is carried out to demonstrate the feasibility of the proposed approach. As always in the analysis of ICSRs, the clinical validity of hypotheses raised with the proposed method must be further reviewed and evaluated by subject matter experts.
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