Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK.
Clinical Trials Unit, Intensive Care National Audit & Research Centre (ICNARC), London, UK.
BMC Med Res Methodol. 2020 Mar 17;20(1):66. doi: 10.1186/s12874-020-00930-2.
Missing data are an inevitable challenge in Randomised Controlled Trials (RCTs), particularly those with Patient Reported Outcome Measures. Methodological guidance suggests that to avoid incorrect conclusions, studies should undertake sensitivity analyses which recognise that data may be 'missing not at random' (MNAR). A recommended approach is to elicit expert opinion about the likely outcome differences for those with missing versus observed data. However, few published trials plan and undertake these elicitation exercises, and so lack the external information required for these sensitivity analyses. The aim of this paper is to provide a framework that anticipates and allows for MNAR data in the design and analysis of clinical trials.
We developed a framework for performing and using expert elicitation to frame sensitivity analysis in RCTs with missing outcome data. The framework includes the following steps: first defining the scope of the elicitation exercise, second developing the elicitation tool, third eliciting expert opinion about the missing outcomes, fourth evaluating the elicitation results, and fifth analysing the trial data. We provide guidance on key practical challenges that arise when adopting this approach in trials: the criteria for identifying relevant experts, the outcome scale for presenting data to experts, the appropriate representation of expert opinion, and the evaluation of the elicitation results.The framework was developed within the POPPI trial, which investigated whether a preventive, complex psychological intervention, commenced early in ICU, would reduce the development of patient-reported post-traumatic stress disorder symptom severity, and improve health-related quality of life. We illustrate the key aspects of the proposed framework using the POPPI trial.
For the POPPI trial, 113 experts were identified with potentially suitable knowledge and asked to participate in the elicitation exercise. The 113 experts provided 59 usable elicitation questionnaires. The sensitivity analysis found that the results from the primary analysis were robust to alternative MNAR mechanisms.
Future studies can adopt this framework to embed expert elicitation within the design of clinical trials. This will provide the information required for MNAR sensitivity analyses that examine the robustness of the trial conclusions to alternative, but realistic assumptions about the missing data.
随机对照试验(RCTs)中数据缺失是不可避免的挑战,特别是在患者报告的结局测量中。方法学指南建议,为避免得出错误的结论,研究应进行敏感性分析,认识到数据可能是“非随机缺失”(MNAR)。一种推荐的方法是征求专家对缺失数据和观察数据的可能结果差异的意见。然而,很少有已发表的试验计划并进行这些启发式练习,因此缺乏进行这些敏感性分析所需的外部信息。本文的目的是提供一个框架,以预测和允许在临床试验的设计和分析中出现 MNAR 数据。
我们开发了一个框架,用于在缺失结局数据的 RCT 中进行和使用专家启发式来制定敏感性分析。该框架包括以下步骤:首先定义启发式练习的范围,其次开发启发式工具,第三征求专家对缺失结局的意见,第四评估启发式结果,第五分析试验数据。我们提供了在试验中采用这种方法时出现的关键实践挑战的指导:确定相关专家的标准,向专家展示数据的结果量表,专家意见的适当表示,以及启发式结果的评估。该框架是在 POPPI 试验中开发的,该试验研究了在 ICU 早期开始进行预防性、复杂的心理干预是否会减少患者报告的创伤后应激障碍症状严重程度,并改善健康相关生活质量。我们使用 POPPI 试验说明了所提出框架的关键方面。
对于 POPPI 试验,确定了 113 名具有潜在合适知识的专家,并邀请他们参加启发式练习。这 113 名专家提供了 59 份可用的启发式问卷。敏感性分析发现,主要分析结果对替代 MNAR 机制具有稳健性。
未来的研究可以采用该框架将专家启发式嵌入临床试验的设计中。这将为 MNAR 敏感性分析提供所需的信息,这些敏感性分析检查了试验结论对缺失数据的替代但现实假设的稳健性。