Department of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Kerpener Str. 62, 50937, Cologne, Germany.
Department of Medical Biometry, Institute for Quality and Efficiency in Health Care, Im Mediapark 8, D-50670 Cologne, Germany.
J Clin Epidemiol. 2021 Jan;129:126-137. doi: 10.1016/j.jclinepi.2020.09.017. Epub 2020 Sep 30.
To provide Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) guidance for the consideration of study limitations (risk of bias) due to missing participant outcome data for time-to-event outcomes in intervention studies.
We developed this guidance through an iterative process that included membership consultation, feedback, presentation, and iterative discussion at meetings of the GRADE working group.
The GRADE working group has published guidance on how to account for missing participant outcome data in binary and continuous outcomes. When analyzing time-to-event outcomes (e.g., overall survival and time-to-treatment failure) data of participants for whom the outcome of interest (e.g., death and relapse) has not been observed are dealt with through censoring. To do so, standard methods require that censored individuals are representative for those remaining in the study. Two types of censoring can be distinguished, end of study censoring and censoring because of missing data, commonly named loss to follow-up censoring. However, both types are not distinguishable with the usual information on censoring available to review authors. Dealing with individuals for whom data are missing during follow-up in the same way as individuals for whom full follow-up is available at the end of the study increases the risk of bias. Considerable differences in the treatment arms in the distribution of censoring over time (early versus late censoring), the overall degree of missing follow-up data, and the reasons why individuals were lost to follow-up may reduce the certainty in the study results. With often only very limited data available, review and guideline authors are required to make transparent and well-considered judgments when judging risk of bias of individual studies and then come to an overall grading decision for the entire body of evidence.
Concern for risk of bias resulting from censoring of participants for whom follow-up data are missing in the underlying studies of a body of evidence can be expressed in the study limitations (risk of bias) domain of the GRADE approach.
为干预研究中因缺失参与者结局数据而导致时间结局的研究局限性(偏倚风险)提供推荐意见的评估、制定和评估(Grading of Recommendations, Assessment, Development, and Evaluation,GRADE)指导。
我们通过迭代过程制定了本指南,该过程包括成员咨询、反馈、展示以及 GRADE 工作组会议上的迭代讨论。
GRADE 工作组已经发布了关于如何在二分类结局和连续性结局中考虑缺失参与者结局数据的指导。当分析参与者的时间结局(例如,总生存和治疗失败时间)数据时,对于未观察到感兴趣结局(例如,死亡和复发)的参与者,通过删失进行处理。为此,标准方法要求删失个体对于研究中仍存活的个体具有代表性。可以区分两种类型的删失,即研究结束时的删失和因缺失数据导致的删失,通常称为失访删失。然而,审查作者可用的常规删失信息无法区分这两种类型。以与在研究结束时可获得完整随访的个体相同的方式处理随访期间数据缺失的个体会增加偏倚风险。在随时间的删失分布(早期删失与晚期删失)、缺失随访数据的总体程度以及个体失访的原因方面,处理臂之间存在相当大的差异,可能会降低研究结果的确定性。由于通常只有非常有限的数据可用,因此,审查和指南作者在判断个别研究的偏倚风险时需要做出透明且经过深思熟虑的判断,然后对整个证据体做出总体分级决策。
对于证据体中基础研究中因缺失随访数据而导致参与者被删失的偏倚风险的关注,可以在 GRADE 方法的研究局限性(偏倚风险)领域中表达。