SignalDetDDI：一种用于在自发报告系统中检测不良药物-药物相互作用的 SAS 宏。
SignalDetDDI: An SAS macro for detecting adverse drug-drug interactions in spontaneous reporting systems.
机构信息
Department of Biostatistics, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan.
Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan.
出版信息
PLoS One. 2018 Nov 19;13(11):e0207487. doi: 10.1371/journal.pone.0207487. eCollection 2018.
Statistical methods for detecting adverse drug reactions (ADRs) resulting from drug-drug interactions (DDIs) have been used in recent years to analyze the datasets in spontaneous reporting systems. We provide the SignalDetDDI macro in SAS to calculate the criteria for detecting ADRs resulting from the concomitant use of two drugs. We outline two criteria for detecting DDIs with the combination of two drugs and illustrate the implementation of the macro by way of an example. To implement the macro, a user specifies the target ADR and the two drugs to be evaluated. The SignalDetDDI macro outputs a table showing the number of reports on ADRs, the values of the two criteria for detecting ADRs, and the presence of DDIs. This macro enables users to easily and automatically assess the clinical DDIs that result from ADRs. The SignalDetDDI macro is freely available in the Supporting Information.
近年来，统计方法已被用于药物-药物相互作用（DDI）所致不良反应（ADR）的检测，以分析自发报告系统中的数据集。我们提供了 SAS 中的 SignalDetDDI 宏，以计算同时使用两种药物时检测 ADR 的标准。我们概述了两种检测两种药物联合使用的 DDI 的标准，并通过示例说明宏的实现。要实现宏，用户需要指定目标 ADR 和要评估的两种药物。SignalDetDDI 宏输出一个表格，显示 ADR 报告的数量、检测 ADR 的两个标准的值以及是否存在 DDI。该宏使用户能够轻松自动评估因 ADR 而导致的临床 DDI。SignalDetDDI 宏可在支持信息中免费获得。
Zotero 插件