摘要
目的在初步探索药品质量风险与药品不良反应(ADR)关联的基础上,通过ADR信号挖掘,为监管机构提供有价值的风险提示。方法建立聚集性风险识别模型,并对分析的结果进行可视化,同时利用河南中心提供的不良反应监测数据对葡萄糖酸钙注射液、胞磷胆碱钠注射液事件进行回顾性分析,对该模型进行验证。结果通过聚集性风险信号识别模型分析2015年3月1日至2015年4月4日国家中心反馈的4 785份河南企业ADR数据,以及2014年3月20日至2014年4月9日的河南中心接收的不良反应数据,进行7天为一个周期的检测,在第一个时间段第4、5周期均检测到YSZY企业葡萄糖酸钙注射液14102421批号的风险信号,第二个时间段第2周期检测到AHLYYY公司的胞磷胆碱注射液130727批号的风险信号,模型分析结果与质量抽检情况较为符合。结论本研究设计的聚集性信号检测识别方法可行,可用于企业品种特定批号风险的初步筛查。考虑到仅采用河南省ADR监测数据,以及对少量案例进行回顾性验证,模型的适用性仍需进一步验证。此外,本研究采用可视化处理使模型输出结果更加直观,满足了监管的实际需求,为以风险为基础的监管提供参考,下一步将继续完善该系统。
Objective To explore the relationship between drug quality risk and adverse drug reaction(ADR)and to provide valuable risk warning for regulators through ADR signal mining.Methods A adverse event cluster signals identification model was established and the results of the analysis were visualized.At the same time,retrospective analysis of calcium gluconate injection and citicoline sodium injection using the adverse reaction monitoring data provided by Henan Center was conducted to verify the model.Results The ADR data of Henan enterprises fed back by the National Center from March 1,2015 to April 4,2015 and the data collected by Henan Center from March 20,2014 to April 9,2014 were analyzed by the cluster signals identification model,respectively.Adverse reactions data were tested for one cycle for 7 days.Risk signals of lot number 14102421 of YSZY calcium gluconate injection were detected in the fourth cycle of the first period.The risk signals of AHLYYY's citicoline 130727 was detected in the second cycle of second period.Results of model analysis were in line with the situation of quality sampling.Conclusion The methods of cluster signals detection and identification designed in this study are feasible and can be used for initial screening of specific batch risk of enterprise varieties.Taking into account only the use of ADR monitoring data in Henan province,as well as a small number of cases retrospective validation,the applicability of the model still needs further verification.In addition,this study uses visual processing to make the output of the model more intuitive,meets the actual needs of regulation and provides a reference for risk-based regulation,and we will continue to improve the system in the next step.
作者
龚立雄
王长之
陈超
杨悦
陈健刚
郭慧
马雪皎
刘超
GONG Li-xiong;WANG Chang-zhi;CHEN Chao;YANG Yue;CHEN Jian-gang;GUO Hui;MA Xue-jiao;LIU Chao(Henan Food and Drug Reevaluation Center,Henan Zhengzhou 450018,China;School of Business Administration,Shenyang Pharmaceutical University,Liaoning Shenyang 110016,China)
出处
《中国药物警戒》
2018年第3期169-175,180,共8页
Chinese Journal of Pharmacovigilance
基金
河南省科技攻关项目(162102310378):河南省药品生产企业药品不良反应监测品种风险分级与风险管理研究
