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| 报告率比例法在中药注射剂不良反应／事件信号提取中的应用 | |
| 引用本文： | 汪海孙,居靖,黄萍,张承绪,侯永芳. 报告率比例法在中药注射剂不良反应／事件信号提取中的应用[J]. 中国药物警戒, 2009, 6(9): 530-533 |
| 作者姓名： | 汪海孙 居靖 黄萍 张承绪 侯永芳 |
| 作者单位： | 1. 安徽省药品检验所,安徽,合肥,230061 2. 安徽医科大学附属安庆医院,安徽,安庆,246003 3. 国家食品药品监督管理局药品评价中心,北京,100045 |
| 基金项目： | 国家食品药品监督管理局药品评价中心国家科技支撑计划课题"中药上市后安全性监测与再评价标准规范研究" |
| 摘 要： | 目的运用报告率比例法（PRR）研究中药注射剂不良反应的特点及规律，以期为发现中药注射剂不良反应的警戒信号提供参考。方法对国家药品不良反应监测中心数据库的33750例中药注射剂不良反应／事件报告作信号检测分析，信号产生的最低阈值：PRR值≥2、卡方值≥4，且至少有3例以上的相关报告。结果33750例报告中，药品一不良反应（Drug-ADR）组合共有21对，涉及16种中药注射剂。结论报告率比例法可以作为有效的工具，为发现中药注射剂不良反应的警戒信号提供参考。 |
| 关 键 词： | 药品不良反应／事件 中药注射剂 PRR信号检测法 药物警戒 |
Use of Proportional Reporting Ratios for Signals Detection from Adverse Drug Reaction/Event of Traditional Chinese Medicine Injection |
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| WANG Hai-sun,JU Jing,HUANG Ping,ZHANG Cheng-xu,HOU Yong-fang. Use of Proportional Reporting Ratios for Signals Detection from Adverse Drug Reaction/Event of Traditional Chinese Medicine Injection[J]. Chinese JOurnal of Pharmacovigilance, 2009, 6(9): 530-533 | |
| Authors: | WANG Hai-sun JU Jing HUANG Ping ZHANG Cheng-xu HOU Yong-fang |
| Affiliation: | 1.Anhui Institute for Drug Control (Anhui Hefei 23006, China) 2Anqing Affiliated Hopistal of Anhui Medical University (Anhui Anqing 246003, China) 3Center for Drug Reevaluation, SFDA (Beijing 100045, China)) |
| Abstract: | Objective To study ADR characteristic and regularity of traditional chinese medicine（TCM） injection, attempt a method of signal detection and provide reference for precaution of TCM injection. Methods 33 750 TCM injection ADR reports were collected by center for drug reevaluation. The minimum criterion for signal is PRR at least 2, chi-squared at least 4, There were at least 3 related reports about them. Results 21 drug-ADR combinations were detected by PRR signal analysis, covered 16 TCM injections. Conclusion The PRR method can serve as an effective tool for the discovery of adverse reactions warning signal for reference. |
| Keywords: | adverse drug reaction/event（ADREADE） traditional Chinese medicine（TCM） injection PRR（ signal detection pharmacovigilance |
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