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离散选择实验应用于2型糖尿病患者治疗偏好的文献分析
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| 篇名： | 离散选择实验应用于2型糖尿病患者治疗偏好的文献分析 |
| TITLE： | Literature Analysis of the Application of Discrete Choice Experiment in the Treatment Preferences of Patient with Type 2 Diabetes |
| 摘要： | 目的：为2型糖尿病患者的临床治疗和药物经济学研究提供参考。方法：以“离散选择”“糖尿病”“Discretechoice”“Dis-creteranking”“Conjointanalysis”“Diabetesmellitus”“Type2”“Type2diabetesmellitus”“Non-insulin-dependentdiabetesmellitus”等为关键词，收集自建库起至2019年12月在中国知网、万方、PubMed、WebofScience等国内外数据库中发表的中英文文献，从属性与水平、DCE选项集、数据质量、样本量、计量经济学分析以及患者偏好结果等6个方面对离散选择实验（DCE）在2型糖尿病患者治疗偏好领域中的应用情况进行梳理总结。结果与结论：共检索到相关文献295篇，其中有效文献30篇。药物管理、血糖控制和低血糖事件是被纳入次数较多的属性；通常采用D-高效设计、D-最优设计或正交设计生成DCE选项集；问卷数据质量可通过问卷内部效度进行检验；样本量一般使用拇指法则进行计算；条件Logit模型、多项Logit模型以及混合Logit模型是最常使用的数据分析模型。相较于轻微的低血糖事件，患者的治疗选择更容易受血糖控制的影响，但当低血糖事件发生在夜间或者程度较重时，患者的治疗偏好往往会发生改变；多数研究纳入了药物管理相关属性，但其并非影响患者治疗偏好的主要因素，且与患者既往服药史密切相关。DCE已被广泛应用于国外2型糖尿病的相关研究中，但在我国应用不多。DCE的数据质量较难控制，虽然构建复杂计量经济学模型的趋势在逐渐上升，但多数研究仍未就样本量确定方法、选项集设计原理、质量控制选项等设计细节予以充分的介绍，且部分研究存在属性数量过多、水平间距过大或过小等不足。建议在设计DCE时可以借鉴BridgesJF等学者在ISPOR报告中提出的开展相关研究的十项标准，以提高设计的严谨性、保证偏好研究结果的可信性。 |
| ABSTRACT： | OBJECTIVE：To provide reference for the clinical treatment and pharmacoeconomics research of type 2 diabetes patients. METHODS ：Using“Discrete choice ”“Discrete ranking ”as Chinese keywords ，“Discrete choice ”“Discrete ranking ” “Conjoint analysis ”“Diabetes mellitus ”“Type 2”“Type 2 diabetes mellitus ”“Non-insulin-dependent diabetes mellitus ”as English keywords，Chinese and English literatures were retrieved from domestic and foreign databases as CNKI ，Wanfang database ， PubMed，Web of Science during the inception to Dec. 2019. The application status of discrete choice experiment （DCE）was analyzed and summarized from the aspect of attributes and levels ，DCE choice sets ，DCE data quality ，sample size ，econometrics analysis and the preference results. RESULTS & CONCLUSIONS ：A total of 295 related literatures were retrieved ，involving 30 valid literatures. The attributes as drug administration ，glucose control and hypoglycemic events were included more frequently. D-efficient/ D-optimal and orthogonal experiment designs were used more frequently to create the DCE choice sets. DCE data quality could be checked by the internal validity tests. The rules of thumb was usually used to calculate the sample size. Conditional Logit model ，multinomial Logit model or mixed Logit model were used more frequently to analyze the preference data. ZH187） Compared with mild hypoglycemic events ，patients’treatment E-mail：19111020032@fudan.edu.cn choices were more likely to be affected by blood glucose control. However ， when hypoglycemic events occurred at：yychen@shmu.edu.cn night or the degree of hypoglycemia was serious ， the ·treatment preference of patients would change. Although most studies included the drug administration related attributes ，they were not major factors influencing patients ’treatment preferences and were closely related to patients ’previous medication history. DCE had been widely used in the study of type 2 diabetes in foreign countries ，but there were few relevant studies in China. The data quality of DCE was difficult to control. Although the trend of building complex econometric models was gradually rising ，most studies had not fully introduced the design details such as sample size determination method ，option set design principle and quality control option. In addition ，there were some deficiencies such as too many attributes ，too large or too small horizontal spacing. It is suggested that the ten criteria of related research in ISPOR report by Bridges JF and other soholars can be used for reference in DCE design to improve the rigor of design and ensure the credibility of preference results. |
| 期刊： | 2020年第31卷第20期 |
| 作者： | 刘世蒙，李顺平，杨毅，唐程翔，陈英耀 |
| AUTHORS： | LIU Shimeng，LI Shunping，YANG Yi，TANG Chengxiang，CHEN Yingyao |
| 关键字： | 2型糖尿病；患者；治疗偏好；离散选择实验 |
| KEYWORDS： | Type 2 Diabetes；Patients；Treatment preferences ；Discrete choice experiment |
| 阅读数： | 494 次 |
| 本月下载数： | 8 次 |
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