We focus on in this paper the convergence rate of the L-N estimators for the fixed effect β in Poisson-Gamma models which are typical hierarchical generalised linear models（HGLMs）. Under the proper assumptions on r...We focus on in this paper the convergence rate of the L-N estimators for the fixed effect β in Poisson-Gamma models which are typical hierarchical generalised linear models（HGLMs）. Under the proper assumptions on response variables and some smoothing conditions, we obtain the strong consistency and the convergence rate of the L-N estimator based on the combination of L-N and quasi-likelihood.展开更多
目的检索美国食品药品监督管理局(Food and Drug Administration,FDA)不良事件报告系统(Adverse Event Reporting System,FAERS)数据库,分析罗莫单抗(Romosozumab)相关药物不良事件(Adverse Drug Event,ADE),为临床用药提供参考。方法...目的检索美国食品药品监督管理局(Food and Drug Administration,FDA)不良事件报告系统(Adverse Event Reporting System,FAERS)数据库,分析罗莫单抗(Romosozumab)相关药物不良事件(Adverse Drug Event,ADE),为临床用药提供参考。方法回顾性查询2019年4月1日至2024年1月31日的美国FAERS数据库,提取Romosozumab相关报告。采用报告比值比(Reporting Odds Ratio,ROR)、比例报告比(Proportional Reporting Ratio,PRR)、贝叶斯可信区间递进神经网络(Bayesian Confidence Propagation Neural Network,BCPNN)和多项式伽马泊松分布缩减(Multi-Item Gamma Poisson Shrinker,MGPS)等方法识别和评估Romosozumab相关ADE。结果共检索到8432351例ADE报告,其中7477例Romosozumab“主要疑似”报告。Romosozumab在16个系统-器官(System Organ Class,SOC)中关联195个ADE信号,主要涉及损伤/中毒、全身性疾病、肌肉骨骼疾病和心脏疾病。常见的ADE包括骨折、骨密度异常、注射部位反应、关节痛、肢体疼痛和心脏事件。此外,一些未在说明书中记载的ADE,如椎体压缩骨折、桡骨骨折、血甲状旁腺素升高和肾功能损害,也显示出较高的信号值。Romosozumab的严重事件包括住院和死亡。结论本研究确认Romosozumab相关的常见ADE,临床需注意未在药品说明书中记载的ADE,如新的骨折或骨密度异常,并采取相应预防措施。展开更多
基金Supported by the National Natural Science Foundation of China(10371005)Scientific Research Funds of the Excellent Young Teachers Program of the Ministry of Education China(VE00074)
文摘We focus on in this paper the convergence rate of the L-N estimators for the fixed effect β in Poisson-Gamma models which are typical hierarchical generalised linear models（HGLMs）. Under the proper assumptions on response variables and some smoothing conditions, we obtain the strong consistency and the convergence rate of the L-N estimator based on the combination of L-N and quasi-likelihood.
