| アブストラクト | BACKGROUND: Drug safety has historically been understudied in pediatric populations, rendering them "therapeutic orphans." Pediatric drug indications and dosages are often inferred by extrapolating safety, efficacy, and dosing data from adult studies, leading to widespread off-label use. However, this approach fails to account for age-specific differences in disease pathophysiology and developmental pharmacokinetics (PK). Despite evidence that adverse drug events (ADEs) manifest with greater severity in pediatric populations than in adults, fewer than 50% of drugs have been systematically studied for pediatric use. The lack of robust drug safety data may result in suboptimal or harmful treatment strategies. METHODS: We used a data-driven approach that integrated three databases -including Merative MarketScan claims, the Maternal and Pediatric Precision in Therapeutics (MPRINT) Knowledgebase (including 670,185 pediatric pharmacoepidemiology, PK, and clinical trial publications on 5062 drugs), the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS, a postmarketing safety surveillance database), and FDA drug label data- to identify high-impact target. High-impact targets were defined as drugs that have a high prescription volume, limited safety evidence and high risk of serious ADEs. RESULTS: With 229,550 prescriptions in MarketScan, only 9 studies, and almost 50 high risk serious ADEs benzonatate was identified as a high-impact drug of concern. Serious ADEs included seizure, death, and arrhythmia with proportional reportion ratios (PRRs) ranging from 4.3 to 477.8. CONCLUSION: Approved in 1958, Benzonatate, a nonnarcotic antitussive agent has a limited safety evidence with only nine PE/PK publications in six decades. Moreover, it is frequently prescribed off-label for cough relief despite questionable effectiveness, and high-risk of serious ADEs. Our findings reveal a disconnect between clinical practice and suppporting safety evidence. As such, there is critical need to study the safety of this drug using emerging real-world data for real-world evidence. In summary, this study presents an approach that is systematic, objective, reproducible, and data driven to identify and prioritize drug-ADE combinations with limited evidence. |
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| 投稿者 | Rahurkar, Saurabh; Ouyang, Jiayi; Jonnalagadda, Pallavi; Liu, Xiaofu; Zhang, Shijun; Chiang, Chien-Wei; Wang, Lei; Shendre, Aditi; Li, Lang |
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| 組織名 | Department of Biomedical Informatics, College of Medicine, The Ohio State;University, Columbus, Ohio, USA.;Center for the Advancement of Team Science, Analytics, and Systems Thinking in;Health Services and Implementation Science Research (CATALYST), The Ohio State |
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