基于不平衡数据处理方法的丹红注射液上市后安全性监测和再评价研究

Post-Marketing Safety Monitoring and Re-Evaluation of Danhong Injection Based on Unbalanced Data Processing Method

目的:建立不平衡数据处理方法对丹红注射液(DHI)临床应用安全性进行再评价,预测临床不良反应发生因素,并为临床合理用药提供参考。方法:首先采用“多中心、大样本”医院集中监测法,收集2009年4月至2013年8月全国6个省内参与监测研究的37家综合性医院30 888例临床使用DHI的住院患者,确定不良反应108例,发生率为3.5‰,属于不平衡数据;基于不平衡数据数理方法,构建重抽样-正则化法,对患者基本信息、患者症状、给药信息和联合用药等信息进行分析处理,确定不良反应相关因素。结果:基于所构建的不平衡数据处理方法,选取6种重抽样-正则化模型,发现随机欠采样和合成小类过采技术组合(比例为3∶3)的重抽样模式较优;以不少于3种模型选中作为筛选条件,共得到41个DHI不良反应相关变量;分析可知,女性、体重指数较小、具有过敏史的患者更易发生不良反应;首次使用DHI的患者更易发生不良反应,联合用药易引发不良反应,但与螺内酯、阿司匹林、盐酸氨溴索和盐酸贝那普利等联合应用或可缓解DHI致不良反应的发生。结论:本研究所构建的重抽样-正则化法可用于处理DHI不良反应的不平衡数据,进而进行上市后安全性再评价及精确预测风险因素,指导临床合理用药及联合用药预警,但所构建的算法是否可用于其他中成药上市后再评价有待进一步研究。

OBJECTIVE: To establish an unbalanced data processing method to re-evaluate the clinical application safety of Danhong injection(DHI), to predict the occurrence factors of clinical adverse drug reactions, so as to provide reference for the rational drug use in clinic. METHODS: Firstly, a “multi-center and large sample” hospital-based surveillance method was used to collect 30 888 inpatients who used DHI from Apr. 2009 to Aug. 2013 in 37 general hospitals in 6 provinces across China, and 108 adverse drug reaction cases were identified, with an incidence of 3.5‰, which belonged to unbalanced data. Based on the unbalanced data processing method, the resampling-regularization method was constructed to analyze and process patients’ basic information, symptoms, drug administration and drug combination to determine the factors associated with adverse drug reactions. RESULTS: Based on the constructed unbalanced data processing method, six resampling-regularization models were selected, and the combination of random under-sampling and synthetic minority over-sampling technique(in the ratio of 3∶ 3) was found to be a better resampling model. A total of 41 DHI adverse drug reaction-related variables were obtained by using no less than three model selections as screening conditions. Analysis showed that women, patients with a lower body mass index and with a history of allergies were more likely to have adverse drug reactions. Patients using DHI for the first time were more likely to have adverse drug reactions, and drug combination was prone to cause adverse drug reactions, yet the combination with spironolactone, aspirin, ambroxol hydrochloride and benazepril hydrochloride might alleviate the occurrence of adverse drug reactions caused by DHI. CONCLUSIONS: The constructed resampling-regularization strategy can be used to deal with the unbalanced data of adverse drug reactions caused by DHI, and then perform post-marketing safety re-evaluation and accurate prediction of risk factors to guide rational clinical use and drug combination warning, yet whether the constructed algorithm can be used for post-marketing re-evaluation of other proprietary Chinese medicines needs further study.