Wang Lian-Xin, Xie Yan-Ming, Cheng Wen-Xiu, Zhong Rou, Zhuang Yun-Ni, Wang Qi
Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences Beijing 100700, China.
Shandong University of Traditional Chinese Medicine Ji'nan 250355, China.
Zhongguo Zhong Yao Za Zhi. 2020 May;45(10):2310-2315. doi: 10.19540/j.cnki.cjcmm.20200221.501.
In recent years, the safety problems and events of traditional Chinese medicine represented by liver injury have occurred frequently. In particular, Polygonum multiflorum has been widely used and considered as a "non-toxic" tonic traditional Chinese medicine for thousands of years. However, in recent years, frequent reports of liver injury events have attracted widespread attention at home and abroad, which has made unfavorable impacts on traditional Chinese medicine and its international development. Some scho-lars have found that susceptible genes of P. multiflorum on liver injury lay a scientific foundation for formulating rational comprehensive prevention and control measures for liver injury risk of P. multiflorum and its relevant preparations. But what are the risk signals of adverse reactions of P. multiflorum in clinical application? Spontaneous reporting system is an important way to monitor and find adverse drug reaction(ADR) signals after the drug is launched in the market. It can find the ADR signals in time and effectively, and then effectively prevent and avoid the occurrence of adverse drug events. At present, the data mining technique has gradually become the main method of ADR/adverse event(AE) report analysis and evaluation at home and abroad. Specifically, Bayesian confidence propagation neural network in Bayesian method is a commonly used risk signal early warning analysis method. In this paper, BCPNN method was used to excavate the risk signals of adverse reactions of Xinyuan Capsules, a traditional Chinese medicine preparation containing P. multiflorum, such as nausea, diarrhea, rash, dizziness, vomiting, abdominal pain, headache, liver cell damage, so as to provide evidence-based evidence for clinical safe and rational use of drugs.
近年来,以肝损伤为代表的中药安全性问题及事件频发。尤其是何首乌,数千年来一直被广泛使用并被视为“无毒”滋补类中药。然而,近年来,肝损伤事件的频繁报道在国内外引起了广泛关注,这对中药及其国际发展产生了不利影响。一些学者发现何首乌肝损伤的易感基因为制定何首乌及其相关制剂肝损伤风险的合理综合防控措施奠定了科学基础。但是何首乌临床应用中不良反应的风险信号有哪些呢?自发报告系统是药物上市后监测和发现药品不良反应(ADR)信号的重要途径。它能够及时、有效地发现ADR信号,进而有效预防和避免药品不良事件的发生。目前,数据挖掘技术已逐渐成为国内外ADR/不良事件(AE)报告分析与评价的主要方法。具体而言,贝叶斯方法中的贝叶斯置信传播神经网络是常用的风险信号预警分析方法。本文运用BCPNN方法挖掘含有何首乌的中药制剂新源胶囊恶心、腹泻、皮疹、头晕、呕吐、腹痛、头痛、肝细胞损伤等不良反应的风险信号,为临床安全合理用药提供循证依据。