基于大型不良反应数据库的他汀类药物安全性分析

发布时间：2018-08-14 18:55

【摘要】：研究目的:①基于美国食品药品监督管理局不良反应自发呈报系统数据库，探讨他汀类药物的使用与认知能力下降，糖尿病及癌症之间的统计学关系。②探索他汀类药物与雷诺嗪合并用药是否会增大横纹肌溶解症的发生风险。研究方法：利用国际上常用的不良反应信号挖掘算法，报告比值比法（ROR），贝叶斯判别区间递进神经网络法（BCPNN），伽玛泊松缩减法（GPS），对不良反应自发呈报系统数据库进行大规模的数据挖掘，明确他汀类药物的使用与认知能力下降，糖尿病及癌症之间的统计学关系。采用Ω收缩法和logistic回归法来探索他汀类药物与雷诺嗪合并用药时发生横纹肌溶解症的风险。研究结果：在分析他汀类药物与认知能力下降之间的关系中，三种不良反应信号挖掘算法的信号检测值分别为2.03，0.80和1.77，即ROR，BCPNN检测到他汀类药物的使用可能会导致患者的认知能力下降；在分析他汀类药物与糖尿病之间的统计学关系中，三种不良反应信号挖掘算法的信号检测值分别为2.42，1.09和2.12，即ROR，BCPNN，GPS均检测到他汀类药物的使用可能会诱发糖尿病；在分析他汀类药与癌症之间的统计学关系中，三种不良反应信号检测算法的信号检测值分别为0.89，-0.17和1.00，即ROR，BCPNN，GPS均没有发现他汀类药物的使用可能会引发癌症。在logistic回归模型中，发现他汀类药物与雷诺嗪合并用药时发生横纹肌溶解症的风险是他汀类药物单用时的3.28倍。Ω收缩法中，omega值为1.51，omega_025值为1.17，表明他汀类与雷诺嗪合并用药会增大横纹肌溶解症的发生风险。通过应用logistic回归法和Ω收缩法，发现他汀类药物和雷诺嗪合并用药可能会增大横纹肌溶解的发生风险。研究结论：美国食品药品监督管理局不良反应自发呈报系统数据库是探索他汀类药物不良反应的有力工具，，临床应用他汀类药物时应注意与之相关的不良反应，尤其是他汀类药物与雷诺嗪合并用药的情况。
[Abstract]:Objective: 1 to explore the use and cognitive decline of statins based on the FDA database of spontaneous notification of adverse reactions. The statistical relationship between diabetes and cancer .2 to explore whether the combination of statins and ranolazine increases the risk of rhabdomyolysis. Methods: using the commonly used adverse reaction signal mining algorithm in the world, Reporting ratio method (ROR), Bayesian discriminant interval progressive neural network method (BCPNN), gamma-Poisson reduction method (GPS), was used to mine large scale data of spontaneous adverse reaction reporting system database, and it was clear that statins use and cognitive ability decreased. The statistical relationship between diabetes and cancer. 惟 contraction and logistic regression were used to explore the risk of rhabdomyolysis when statins were combined with ranolazine. Results: in analyzing the relationship between statins and cognitive decline, The detection values of the three adverse reaction signal mining algorithms were 2.030.80 and 1.77, respectively. RORBCPNN showed that the use of statins might lead to a decrease in cognitive ability of patients, and in the analysis of the statistical relationship between statins and diabetes, The detection values of the three adverse reaction signal mining algorithms were 2.42 / 1.09 and 2.12, respectively, i.e., the use of statins detected by RORBCPNN GPS could induce diabetes mellitus, and in analyzing the statistical relationship between statins and cancer, The signal detection values of the three adverse reaction signal detection algorithms were 0.89- 0.17 and 1.00 respectively. RORBCPNN- GPS did not find that the use of statins might lead to cancer. In the logistic regression model, The risk of rhabdomyolysis of statins combined with ranolazine was 3.28 times higher than that of statins alone. Omega value of omega in 惟 contraction method was 1.51 omega 0.25, indicating that statins combined with ranolazine could increase the rhabdomyolysis of rhabdomyolysis. The risk of dissolution. By using logistic regression method and 惟 contraction method, it was found that the combination of statins and ranolazine may increase the risk of rhabdomyolysis. Conclusion: the FDA database of spontaneous reporting of adverse reactions is a powerful tool for exploring the adverse reactions of statins, and the clinical application of statins should pay attention to the related adverse reactions. Especially the combination of statins and ranolazine.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R95

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