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A Computational Framework for Identifying Age Risks in Drug-Adverse Event Pairs.
Zhizhen Zhao1, Ruoqi Liu2,3, Lei Wang3
1Department of Statistics, The Ohio State University, Columbus, Ohio, USA.
Summary
This study identifies specific drug-adverse drug event (ADE) pairs posing higher risks for certain age groups. Researchers developed a framework to analyze patient data, highlighting age-related susceptibilities in drug safety surveillance.
Area of Science:
- Pharmacovigilance
- Computational Statistics
- Drug Safety
Background:
- Identifying drug-adverse drug event (ADE) associations is vital for drug safety.
- Children and seniors are known to be more susceptible to ADEs.
- Comprehensive analysis of age-specific risks in drug-ADE pairs is limited.
Purpose of the Study:
- To develop a statistical framework for detecting age groups susceptible to specific ADEs from drug use.
- To quantify age-related risks associated with drug-ADE pairs.
- To identify high-risk drug-ADE pairs for different age demographics.
Main Methods:
- Utilized the FDA Adverse Event Reporting System (FAERS) database (2004-2018Q3).
- Employed Chi-squared tests and disproportionality analysis to detect age-related differences in drug-ADE pairs.
- Analyzed over 4.5 million drug-ADE pairs.
Main Results:
- Identified 2,523 drug-ADE pairs exhibiting the highest age-related risk.
- Developed a computational framework for identifying age-specific drug risks.
- Conducted a case study on statin-induced ADEs in pediatric populations.
Conclusions:
- The developed framework effectively identifies age-specific risks in drug-ADE associations.
- Findings contribute to enhanced drug safety surveillance by highlighting vulnerable populations.
- Results provide valuable insights for personalized medicine and risk management strategies.
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