论文标题
应对信息丢失和使用辅助数据来源：NISS Ingram Olkin论坛系列的报告未计划的临床试验中断
Coping with Information Loss and the Use of Auxiliary Sources of Data: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions
论文作者
论文摘要
临床试验的破坏始终代表了介入研究结束的不可忽视的一部分。尽管SARS-COV-2（COVID-19）大流行导致了临床研究的令人印象深刻且前所未有的启动，但它也导致了其他疾病地区的临床试验大量中断，在大流行期间，大约80％的非COVID-19试验被停止或中断。在许多情况下，被破坏的试验将没有计划的统计能力来产生可解释的结果。本文介绍了通过合并辅助数据源可用的其他信息来弥补试验中断引起的信息损失的方法。所描述的方法包括使用基线和早期结果数据的辅助数据，以及从试验本身获得的，以及从外部数据源中纳入信息的常见主义者和贝叶斯方法。该方法通过应用于基于初级保健儿科学习活动营养（PLAN）研究的人工数据的分析，这是一项评估超重儿童饮食和运动干预的临床试验，受到了COVID-19的大流行的影响。我们展示了所有提出的方法如何导致相对于仅使用完整案例数据的精度提高。
Clinical trials disruption has always represented a non negligible part of the ending of interventional studies. While the SARS-CoV-2 (COVID-19) pandemic has led to an impressive and unprecedented initiation of clinical research, it has also led to considerable disruption of clinical trials in other disease areas, with around 80% of non-COVID-19 trials stopped or interrupted during the pandemic. In many cases the disrupted trials will not have the planned statistical power necessary to yield interpretable results. This paper describes methods to compensate for the information loss arising from trial disruptions by incorporating additional information available from auxiliary data sources. The methods described include the use of auxiliary data on baseline and early outcome data available from the trial itself and frequentist and Bayesian approaches for the incorporation of information from external data sources. The methods are illustrated by application to the analysis of artificial data based on the Primary care pediatrics Learning Activity Nutrition (PLAN) study, a clinical trial assessing a diet and exercise intervention for overweight children, that was affected by the COVID-19 pandemic. We show how all of the methods proposed lead to an increase in precision relative to use of complete case data only.
