Signal detection statistics of adverse drug events in hierarchical structure for matched case–control data

Author:

Heo Seok-Jae1,Jeong Sohee1,Jung Dagyeom1,Jung Inkyung1ORCID

Affiliation:

1. Division of Biostatistics, Department of Biomedical Systems Informatics, Yonsei University College of Medicine , Seoul 03722, Korea

Abstract

Summary The tree-based scan statistic is a data mining method used to identify signals of adverse drug reactions in a database of spontaneous reporting systems. It is particularly beneficial when dealing with hierarchical data structures. One may use a retrospective case–control study design from spontaneous reporting systems (SRS) to investigate whether a specific adverse event of interest is associated with certain drugs. However, the existing Bernoulli model of the tree-based scan statistic may not be suitable as it fails to adequately account for dependencies within matched pairs. In this article, we propose signal detection statistics for matched case–control data based on McNemar’s test, Wald test for conditional logistic regression, and the likelihood ratio test for a multinomial distribution. Through simulation studies, we demonstrate that our proposed methods outperform the existing approach in terms of the type I error rate, power, sensitivity, and false detection rate. To illustrate our proposed approach, we applied the three methods and the existing method to detect drug signals for dizziness-related adverse events related to antihypertensive drugs using the database of the Korea Adverse Event Reporting System.

Funder

National Research Foundation of Korea

Korea government

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

Reference30 articles.

1. A Bayesian neural network method for adverse drug reaction signal generation;Bate;European Journal of Clinical Pharmacology,1998

2. Bayesian data mining in large frequency tables, with an application to the FDA spontaneous reporting system;DuMouchel;The American Statistician,1999

3. Use of proportional reporting ratios (PRRS) for signal generation from spontaneous adverse drug reaction reports;Evans;Pharmacoepidemiology and Drug Safety,2001

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3