Guideline on missing data in confirmatory clinical trials
Guideline on missing data in confirmatory clinical trials
复制标题
验证性临床试验缺失数据指南
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Z. Jing
中科院分区：
文献类型：
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作者：
Z. Jing
缺失数据是验证性临床试验研究中不可避免的问题,缺失数据的处理方法是影响试验结论客观性的重要因素。临床试验中的数据缺失主要是由脱落引起的,按机制可分为完全随机缺失(MCAR)、随机缺失(MAR)和非随机缺失(MNAR)。通过完整的病例分析、精心选择缺失处理方法可以减少试验结论的偏倚。针对这一问题，欧洲药品评价机构（EMEA）发布了验证性临床试验数据缺失的指南，现已生效。本文围绕该指南，介绍了临床试验中缺失数据处理的主要方法，旨在为我国的药物开发和临床研究提供参考。
Missing data is an unavoidable problem in the research of confirmatory clinical trials,and the approach for handling missing data is an important factor affecting the objectivity of the trial conclusions.The data missing in the clinical trial is mainly induced by drop-out,which could be classified as missing completely at random(MCAR),missing at random(MAR) and missing not at random(MNAR) according to the mechanism.The bias of trial conclusion could be reduced through the complete case analysis,careful selection of the method handling for missing data(e.g.,imputation and mixed models) and the sensitivity analysis.To address this issue,European Medicines Evaluation Agency(EMEA) published a guideline on the missing data in the confirmatory clinical trial,and now it had come into effect.With focus on this guideline,we presented the main methods for handling missing data in clinical trials in this paper with the aim providing information for the drug development and clinical research in China.