中国药物警戒 ›› 2025, Vol. 22 ›› Issue (1): 10-15.
DOI: 10.19803/j.1672-8629.20240911

• 药源性血小板减少研究专栏 • 上一篇    下一篇

基于多源信息构建药品不良反应基准数据库

聂晓璐1,2,3, 孙凤2,3, 阎爱侠4, 彭晓霞1,3#, 詹思延2,*   

  1. 1国家儿童医学中心,首都医科大学附属北京儿童医院临床流行病与循证医学中心, 100045;
    2北京大学公共卫生学院流行病与卫生统计学系,北京 100091;
    3海南省真实世界数据研究院,海南 琼海 571437;
    4北京化工大学生命科学与技术学院,北京 100029
  • 收稿日期:2024-11-25 出版日期:2025-01-15 发布日期:2025-01-22
  • 通讯作者: *詹思延,教授·博导,药物流行病学与循证医学。E-mail: siyan-zhan@bjmu.edu.cn#为共同通信作者。
  • 作者简介:聂晓璐,女,副研究员,药物流行病学与循证医学。
  • 基金资助:
    国家自然科学基金资助项目(82204149); 北京市医院管理中心“青苗”计划专项经费资助(QML20231204); 北京儿童医院科研苗圃计划(3-1-014-01-04); 海南博鳌乐城国际医疗旅游先行区真实世界研究专项计划项目(HNLC 2022RWS015)

Methodology for Constructing Benchmark Database of Adverse Drug Reactions Based on Multi-Source Information

NIE Xiaolu1,2,3, SUN Feng2,3, YAN Aixia4, PENG Xiaoxia1,3#, ZHAN Siyan2,*   

  1. 1Center for Clinical Epidemiology & Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China;
    2Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100091, China;
    3Hainan Institute of Real World Data, Qionghai Hainan 571437, China;
    4College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2024-11-25 Online:2025-01-15 Published:2025-01-22

摘要: 目的 总结现有主要药品不良反应(ADR)基准数据库构建信息来源,并以药源性血小板减少(DITP)为例综合多源数据构建ADR基准数据库,以期为今后开展计算模拟研究和指导临床安全用药提供参考。方法 比较介绍现有各主要ADR基准数据库的信息来源优势与局限性;利用多源信息汇总构建DITP基准数据库,使用Kappa值评价各来源数据信息的一致性;利用药品解剖学、治疗学及化学分类法(ATC)编码分析DITP风险药物在解剖学分类中的分布情况与差异。结果 利用美国食品药品监督管理局(FDA)推荐的多源信息来源方法构建了包含1 765种药物的DITP基准数据库(DITPst)。在DITPst数据库中,按照ATC编码解剖学分类划分,最常发生DITP的药物为抗肿瘤及免疫调节类药物,77.17%(196/254)可引起DITP。结论 利用多源信息构建ADR基准数据库可为药物研发开展计算模拟研究及药品上市后安全与合理用药提供数据参考。

关键词: 药品不良反应, 药源性血小板减少, 基准数据库, 多源信息, 计算模拟研究, 抗肿瘤药物, 免疫调节类药物, 安全合理用药

Abstract: Objective To summarize the primary data sources used in constructing benchmark databases for adverse drug reactions (ADR) and to demonstrate a comprehensive, multi-source approach to building an ADR benchmark database using drug-induced thrombocytopenia (DITP) as an example so as to provide a reference for future computational modeling studies and to guide safer clinical drug use. Methods The advantages and limitations of the data sources used in existing ADR benchmark databases were compared and analyzed. A benchmark database for DITP was constructed by integrating data from multiple sources, and the consistency of these data sources was evaluated using the kappa statistic. The distribution and variability of DITP-risk drugs were analyzed based on the Anatomic Therapeutic Chemical (ATC) classification system. Results Using the FDA-recommended multi-source integration approach, a DITP benchmark database (DITPst) comprising 1 765 drugs was constructed. Analysis of the anatomical classification of drugs within the DITPst database revealed that antineoplastic and immunomodulating agents were the most frequently associated with DITP, with 77.17% (196/254) of these drugs identified as causing these ADR. Conclusion Constructing ADR benchmark databases using multi-source information provides a valuable data reference for computational modeling in drug development as well as for ensuring post-marketing drug safety and promoting rational drug use.

Key words: Adverse Drug Reaction, Drug-Induced Thrombocytopenia, Benchmark Database, Multi-Source Data, Computational Simulation Research, Antineoplastic Drug, Immunomodulating Drug, Safe and Rational Drug Use

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