Application of Association Rules Analysis in Mining Adverse Drug Reaction Signals

Adverse drug reactions (ADRs) are increasingly becoming a serious public health problem. Spontaneous reporting systems (SRSs) are an important way for many countries to monitor ADRs produced in the clinical use of drugs, and they are the main data source for ADR signal detection. The traditional sig...

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Bibliographic Details
Published in:Applied sciences 2021-11, Vol.11 (22), p.10828
Main Authors: Wei, Jianxiang, Dai, Jimin, Zhao, Yingya, Han, Pu, Zhu, Yunxia, Huang, Weidong
Format: Article
Language:English
Subjects:
adverse drug reaction
Algorithms
association rule
Associations
Contingency
Data mining
Decision making
Drugs
Experimental methods
Mining accidents & safety
Monitoring systems
Performance evaluation
Pharmacovigilance
Product safety
Public health
Regulatory agencies
Side effects
Signal detection
Statistical analysis
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Summary:Adverse drug reactions (ADRs) are increasingly becoming a serious public health problem. Spontaneous reporting systems (SRSs) are an important way for many countries to monitor ADRs produced in the clinical use of drugs, and they are the main data source for ADR signal detection. The traditional signal detection methods are based on disproportionality analysis (DPA) and lack the application of data mining technology. In this paper, we selected the spontaneous reports from 2011 to 2018 in Jiangsu Province of China as the research data and used association rules analysis (ARA) to mine signals. We defined some important metrics of the ARA according to the two-dimensional contingency table of ADRs, such as Confidence and Lift, and constructed performance evaluation indicators such as Precision, Recall, and F1 as objective standards. We used experimental methods based on data to objectively determine the optimal thresholds of the corresponding metrics, which, in the best case, are Confidence = 0.007 and Lift = 1. We obtained the average performance of the method through 10-fold cross-validation. The experimental results showed that F1 increased from 31.43% in the MHRA method to 40.38% in the ARA method; this was a significant improvement. To reduce drug risk and provide decision making for drug safety, more data mining methods need to be introduced and applied to ADR signal detection.
ISSN:2076-3417
2076-3417
DOI:10.3390/app112210828