国内药物不良反应信号检测文献中数据挖掘问题的调查和分析  

Investigation and analysis on data mining problems in adverse drug reaction signal detection study in China

作　　者：戴睿 张青霞[3] 胡扬[1] 谢昊[1] 王焕玲 赵彬[1] 合理用药国际网络中国中心组临床安全用药组 Dai Rui;Zhang Qingxia;Hu Yang;Xie Hao;Wang Huanling;Zhao Bin;Medication Safety Panel in China Core Group of International Network for the Rational Use of Drugs(Department of Pharmacy,Peking Union Medical College Hospital,Peking Union Medical College,Chinese Academy of Medical Sciences,Beijing 100730,China;Clinical Pharmacology Research Center,Peking Union Medical College Hospital,Peking Union Medical College,Chinese Academy of Medical Sciences,Beijing 100730,China;Department of Pharmacy,Xuanwu Hospital,Capital Medical University,National Clinical Research Center for Geriatric Disease,Beijing 100053,China;不详)

机构地区：[1]中国医学科学院北京协和医学院北京协和医院药剂科,北京100730 [2]中国医学科学院北京协和医学院北京协和医院临床药理研究中心,北京100730 [3]首都医科大学宣武医院药学部,国家老年疾病临床医学研究中心,北京100053 [4]不详

出　　处：《药物不良反应杂志》2023年第12期717-723,共7页Adverse Drug Reactions Journal

基　　金：北京协和医院中央高水平医院临床科研专项(2022-PUMCH-B-058);中国药学会医院药学专业委员会人才专项资助项目(CPA-Z05-ZC-2022-003)。

摘　　要：目的了解我国当前药物不良反应(ADR)/不良事件(AE)信号检测研究文献中数据挖掘方面存在的问题。方法检索中国生物医学文献服务系统、中国知网、万方医学和维普网关于ADR/AE信号检测类研究的文献(截至2022年5月30日)。将数据挖掘部分的相关内容从以下4个维度和9个条目进行调查和评价。(1)背景数据,包括1个条目;(2)数据预处理,包括药物映射、AE映射、缺失值处理和数据去重4个条目;(3)数据挖掘算法(DMA),包括DMA选择、DMA公式解读和信号阈值3个条目;(4)结果解读,包括1个条目。按照数据挖掘相关规范和技术要求,以文献中4个维度和9个条目的报告/报告无误率作为总体质量评价指标,报告/报告无误率≥60%为总体质量达到优良水平。结果共纳入165篇文献。背景数据维度采用了全数据库所有其他药物数据的文献报告/报告无误率为35.2%(58/165),未达到优良水平。数据预处理维度中进行了药物映射、AE映射、缺失值处理和数据去重的文献报告/报告无误率分别为22.4%(37/165)、73.9%(122/165)、10.3%(17/165)和55.2%(91/165),该维度的报告/报告无误率为40.5%(267/660),未达到优良水平,仅其中的AE映射条目达到优良水平。DMA维度中≥2种DMA、DMA公式解读和信号阈值的文献报告/报告无误率分别为63.6%(105/165)、78.2%(129/165)和87.9%(145/165),该维度的报告/报告无误率为76.6%(379/495),均达到优良水平。结果解读的报告/报告无误率为87.4%(144/165),达到优良水平,其中7篇将信号解读为"阳性"或"阴性"信号,14篇对信号意义的解释采用了因果关系的描述。165篇文献的4个维度共9个条目的总体报告/报告无误率为57.1%(848/1485),未达到优良水平。结论国内ADR/AE信号检测研究的文献中主要问题为背景数据的选择和数据预处理不足,提示我国相关研究应在这2个维度方面改进,提高ADR/AE信号检测研究的质量。Objective To understand the problems of data mining in adverse drug reaction(ADR)/adverse event(AE)signal detection study in China.Methods The literature on ADR/AE signal detection study in SinoMed,CNKI,WanFang Data and VIP databases were retrieved(up to May 30,2022).The relevant content of the data mining in the literature was investiagted and evaluated from the following 4 dimensions and 9 items:(1)background data,including 1 item;(2)data preprocessing,including 4 items such as drug mapping,AE mapping,missing value processing,and data deduplication;(3)data mining algorithm(DMA),including 3 items such as DMA selection,DMA formula interpretation,and signal threshold;(4)interpretation of the results,including 1 item.According to the relevant specifications and technical requirements of data mining,the reporting/reporting error-free rate of the 4 dimensions and 9 items in the literature was taken as the overall quality evaluation index.Reporting/reporting error-free rate≥60%was considered to be an excellent level of overall quality.Results A total of 165 articles were included.On the background data dimension,the reporting/reporting error-free rate of using all the other drug data of the entire database in the literature was 35.2%(58/165),which did not reach an excellent level.On the data preprocessing dimension,the reporting/reporting error-free rates of drug mapping,AE mapping,missing value processing,and data deduplication in the literature were 22.4%(37/165),73.9%(122/165),10.3%(17/165),and 55.2%(91/165),respectively.The reporting/reporting error-free rate on this dimension was 40.5%(267/660),which did not reach the excellent level,only the rate of AE mapping reached the excellent level.On the DMA dimension,the reporting/reporting error-free rates of≥2 DMA,DMA formula interpretation,and signal threshold in the literature were 63.6%(105/165),78.2%(129/165),and 87.9%(145/165),respectively.The reporting/reporting error-free rate on this dimension was 76.6%(379/495),which reached an excellent level.The reportin

关 键 词：药物警戒 药物相关副作用和不良反应 药物不良反应报告系统 信号检测 数据挖掘 评价性研究 

分 类 号：R969[医药卫生—药理学]