基于贝叶斯方法两种药物治疗脑梗塞（后遗症期）成本效果模型构建研究

发布时间：2017-12-27 17:04

本文关键词：基于贝叶斯方法两种药物治疗脑梗塞（后遗症期）成本效果模型构建研究　出处：《北京中医药大学》2015年硕士论文　论文类型：学位论文

【摘要】：目的：本研究旨在将贝叶斯理论(Bayes' theorem)评价方法引入脑梗塞药物经济学(Pharmacoeconomics, PE)评价中。通过构建贝叶斯效果、成本和成本-效果评价模型,并收集患者相关用药信息数据,评价药物A和药物B在有效性、经济性两方面的综合效果,对比贝叶斯方法和经典统计学在药物经济学研究中的差异,拓宽研究思路,丰富研究方法,以期更好地指导临床合理用药。方法：本研究选取总病例数104例,其中单独使用药物A病例71例,单用药物B病例33例。以有效性和经济性为评价维度,分别选取美国国立卫生研究院卒中量表(National Institute of Health stroke scale, NIHSS)评分改善有效率、中医证候评分改善有效率和疾病治疗成本3项指标构建贝叶斯药物经济学评价模型。根据评价指标的不同性质,选用不同的分布类型进行抽样模拟。结果：两单独用药方案组在年龄、性别方面均具备可比性。贝叶斯方法分析可以得出：效果方面,NIHSS评分改善有效率,药物A为0.7739[0.6711,0.8623],药物B为0.8164[0.6709,0.9257],差值为-0.04243[-0.195,0.1272],无统计学差异；中医证侯评分改善有效率,药物A为0.8723[0.7859,0.9386],药物B为0.4849[0.3192,0.6527],差值为0.3874[0.1998,0.569],差异有统计学意义。治疗成本方面,药物A为2758.0[2528.0,3006.0]元,药物B为3474.0[3157.0,3821.1]元,差值为-715.4[-1131.0,-713.1]元,差异有统计学意义。成本-效果方面,NIHSS评分改善有效率成本-效果值,药物A为3579.0[3094.0,4204.0],药物B为4287.0.0[5251.0,11080.0]；中医证侯评分改善有效率成本-效果值,药物A为3169.0[2815.0,3610.0],药物B为7411.0[5226.0,11080.0]。结论：药物A与药物B相比,药物A的成本-效果优于药物B,因此应优先选择药物A作为脑梗塞的治疗药物,从而获得较优的经济效益。本研究基于贝叶斯原理,通过Winbugs软件建立了药物经济学中效果(有效率)、成本、成本-效果的模型,在一定程度上为药物经济学分析提供了新的模型思路。贝叶斯方法综合了先验信息、总体信息和样本信息,结果直观、精确、全面,是对经典统计中药物经济学分析的重要补充。
[Abstract]:Objective: the purpose of this study was to introduce the Bias theory (Bayes'theorem) evaluation method into the Pharmacoeconomics (PE) evaluation of cerebral infarction. Through the construction of Bayesian effect and effect evaluation of cost and cost model, and collect relevant information data in patients with medication, comprehensive effect evaluation of drug A and drug B in the effectiveness and economy of the two aspects, compared with Bayesian methods and classical statistics in pharmacoeconomics research in difference, broaden research ideas, enrich the research methods, in order to to better guide the clinical rational use of drugs. Methods: the total number of cases was selected in 104 cases, including 71 cases of drug A and 33 cases of single drug B. The effective and economical evaluation dimensions, were selected for the National Institutes of Health Stroke Scale (National Institute of Health stroke scale, NIHSS) score improved efficiency, TCM syndrome score improved treatment efficiency and disease cost in constructing the economic evaluation model of 3 indicators of Bayesian agents. According to the different properties of the evaluation index, different types of distribution are selected to carry out sampling simulation. Results: two the age and sex were comparable in the group of individual drugs. Bias analysis can be drawn: the effect, NIHSS score improved efficiency, drug A 0.7739[0.6711,0.8623], drug B 0.8164[0.6709,0.9257], difference -0.04243[-0.195,0.1272], no significant difference; the TCM syndrome score improved efficiency, drug A 0.8723[0.7859,0.9386], drug B 0.4849[0.3192,0.6527], the difference is 0.3874[0.1998,0.569], the difference was statistically significant. In terms of treatment cost, the drug A is 2758.0[2528.03006.0] yuan, the drug B is 3474.0[3157.03821.1] yuan, the difference is -715.4[-1131.0, -713.1] yuan, the difference is statistically significant. In terms of cost effectiveness, the NIHSS score improved the cost effective value of effective rate, the drug A was 3579.0[3094.04204.0], the drug B was 4287.0.0[5251.011080.0], the TCM syndrome score improved the effective rate cost effectiveness value, the drug A was 3169.0[2815.03610.0], and the drug B was 7411.0[5226.011080.0]. Conclusion: compared with drug B, the cost effectiveness of drug A is better than that of drug B, so we should give priority to the selection of drug A as a treatment drug for cerebral infarction, so as to get better economic benefits of drug A. Based on Bayes principle, this study established a pharmacoeconomic effect (efficiency), cost and cost-effectiveness model based on Bayesian theory, and to some extent, it provided a new model for Pharmacoeconomics analysis. Winbugs The Bias method integrates the prior information, the general information and the sample information. The result is intuitive, accurate and comprehensive, which is an important supplement to the pharmacoeconomics analysis of classical statistics.
【学位授予单位】：北京中医药大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：R743.33

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