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Identification of populations likely to benefit from pharmacogenomic testing

机译:鉴定药物可能受益于药物替代试验

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摘要

Objectives Pharmacogenomic testing (PGX) implementation is rapidly expanding, including pre-emptive testing funded by health systems. PGX continues to develop an evidence base that it saves money and improves clinical outcomes. Identifying the potential impact of pre-emptive testing in specific populations may aid in the development of a business case. Methods We utilized a software tool that can evaluate patient drug lists and identified groups of patients most likely to benefit from implementation of a PGX testing program in a major medical system population. Results Medication lists were obtained for sixteen patient groups with a total of 82 613 patients. The percent of patients in each group with testing ‘Recommended’, ‘Strongly recommended’, or ‘Required’ ranged from 12.7% in the outpatient pediatric psychiatry group to 75.7% in the any adult inpatient age >50 years group. Some of the highest yield drugs identified were citalopram, simvastatin, escitalopram, metoprolol, clopidogrel, tramadol, and ondansetron. Conclusion We demonstrate a significant number of patients in each group may have benefit, but targeting certain ones for pre-emptive testing may result in the initial highest yield for a health system.
机译:目标药物基因组测试(PGX)的实施正在迅速扩大,包括由卫生系统资助的先发制人测试。PGX继续开发一个证据库,以节省资金并改善临床结果。识别特定人群中先发制人测试的潜在影响可能有助于商业案例的开发。方法我们使用一个软件工具,可以评估患者药物清单,并确定在主要医疗系统人群中最有可能受益于实施PGX检测计划的患者群体。结果获得16个患者组的药物清单,共82613名患者。在每一组中,接受“推荐”、“强烈推荐”或“必需”检测的患者百分比从门诊儿科精神病学组的12.7%到任何年龄>50岁的成人住院患者组的75.7%不等。一些产量最高的药物包括西酞普兰、辛伐他汀、艾司西酞普兰、美托洛尔、氯吡格雷、曲马多和昂丹司琼。结论我们证明,每组中有相当数量的患者可能受益,但针对某些患者进行先发制人的检测可能会导致卫生系统最初的最高收益。

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  • 来源
    《Pharmacogenetics and genomics》 |2020年第5期|共5页
  • 作者单位

    Divisions of Medical Toxicology &

    Precision Medicine and Clinical Data Analytics and Decision;

    Division of Clinical Data Analytics and Decision Support Department of Medicine University of;

    Divisions of Medical Toxicology &

    Precision Medicine and Clinical Data Analytics and Decision;

    Division of Clinical Data Analytics and Decision Support Department of Medicine University of;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 药学;
  • 关键词

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