MISSING DATA HANDLING METHODS IN MEDICAL DEVICE CLINICAL TRIALS
MISSING DATA HANDLING METHODS IN MEDICAL DEVICE CLINICAL TRIALS
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DOI：
10.1080/10543400903243009
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发表时间：
2009-01-01
影响因子：
1.1
通讯作者：
Li, Ning
中科院分区：
文献类型：
--
作者：
Yan, Xu;Lee, Shiowjen;Li, Ning
临床试验分析的主要问题之一是由于患者在研究完成前退出而导致的数据缺失。缺失数据的问题可能导致有偏见的治疗比较，并可能影响研究结果的解释。由于缺失数据的机制在大多数情况下是未知和不可验证的，监管机构经常要求各种敏感性分析来处理缺失数据，以评估研究结果的稳健性。本文讨论了用于处理医疗器械临床试验中缺失数据的方法，重点介绍了临界点分析作为评估缺失数据影响的一般方法。引爆点是导致研究结论改变的结果。这些结果可以传达给临床审查员，以确定它们是否令人难以置信地不利。该分析有助于临床评价人员对研究中的治疗效果做出判断。包括三个具有合理代表性的丢失数据率范围的示例来说明所提到的方法。
One of the major problems in the analysis of clinical trials is missing data caused by patients dropping out before study completion. The issue of missing data can result in biased treatment comparisons and can impact the interpretation of study results. Since the missing data mechanism is unknown and unverifiable in most situations, regulatory agencies often request various sensitivity analyses for handling missing data to evaluate the robustness of study results. This article discusses methods used to handle missing data in medical device clinical trials, focusing on tipping-point analysis as a general approach for the assessment of missing data impact. Tipping points are outcomes that result in a change of study conclusion. Such outcomes can be conveyed to clinical reviewers to determine if they are implausibly unfavorable. The analysis aids clinical reviewers in making judgment regarding treatment effect in the study. Three examples with a reasonably representative range of missing data rate are included to illustrate the methods referred.