Flyer Paul, Hirman Joseph
Department of Biostatistics, Pacific Northwest Statistical Consulting, Inc., Woodinville, Washington, USA.
J Biopharm Stat. 2009 Nov;19(6):969-79. doi: 10.1080/10543400903242746.
Missing data for key efficacy and safety endpoints in clinical trials have the potential to undermine the scientific integrity of the study and prevent definitive conclusions regarding the safety and efficacy of an experimental product. Much of the missing data is the result of poor protocol design and a lack of agreement in the scientific community regarding the collection of study data after treatment discontinuation instead of an inability to collect the data. Rather than dealing with the fundamental causes of missing data, the statistical community has traditionally attempted to explicitly impute the missing data based upon observed data or more recently through the use of statistical models that implicitly impute the missing data. In this article, the causes for missing data are described and a number of approaches to maintain the integrity of the studies are described.
临床试验中关键疗效和安全性终点的缺失数据有可能破坏研究的科学完整性,并妨碍就实验产品的安全性和有效性得出明确结论。许多缺失数据是方案设计不佳以及科学界在治疗中断后研究数据收集方面缺乏共识所致,而非无法收集数据。统计界传统上不是处理缺失数据的根本原因,而是试图根据观察到的数据明确估算缺失数据,或者最近通过使用隐含估算缺失数据的统计模型来进行估算。本文描述了缺失数据的原因,并介绍了一些维护研究完整性的方法。