Development of a practical approach to expert elicitation for randomised controlled trials with missing health outcomes: Application to the IMPROVE trial.
Development of a practical approach to expert elicitation for randomised controlled trials with missing health outcomes: Application to the IMPROVE trial.
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DOI：
10.1177/1740774517711442
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发表时间：
2017-08
期刊：
影响因子：
--
通讯作者：
Carpenter J
中科院分区：
文献类型：
--
作者：
Mason AJ;Gomes M;Grieve R;Ulug P;Powell JT;Carpenter J
缺失数据的随机对照试验的分析通常假设，在对观察数据进行调节后，缺失数据的概率不取决于患者的结局，因此数据是“随机缺失”的。例如，这种假设通常是不可信的，因为健康状况相对较差的患者可能更容易辍学。方法学指南建议，试验需要敏感性分析，这是最好的信息来自专家意见，以评估结论是否稳健的缺失数据的替代假设。在实践中实施这些方法的一个主要障碍是缺乏征求专家意见的相关实用工具。我们开发了一种新的实用工具，以引起专家的意见，并证明其用于随机对照试验的缺失数据。我们通过IMPROVE试验（ISRCTN 48334791）开发并说明了我们的方法，该试验是一项正在进行的多中心随机对照试验，比较了腹主动脉瘤破裂患者的紧急血管内策略与开放式修复术。在IMPROVE试验中，随机化后3个月，21%的存活患者未完成健康相关生活质量问卷（通过EQ-5D-3L评估）。我们通过开发一个基于网络的工具来解决这个问题，该工具提供了一种实用的方法，用于获取关于缺失与完整数据患者之间生活质量差异的专家意见。我们展示了专家意见如何在一个完全贝叶斯框架内定义信息先验，以进行敏感性分析，使缺失的数据依赖于未观察到的患者特征。在应邀参加的46名专家中，共有26名专家完成了征求意见活动。缺失数据的患者的生活质量评分平均低于完整数据的患者，但这些得出的值存在相当大的不确定性。随机缺失分析发现，随机分配至急诊血管内策略组的患者的平均（95%可信区间）生活质量评分高于开放性修复组，为0.062（-0.005至0.130）。我们的敏感性分析使用了提取的专家信息作为汇总先验，发现急诊血管内策略与开放性修复术相比，平均生活质量提高了0.076（-0.054至0.198）。我们提供并验证了一个实用的工具，用于获取随机对照试验敏感性分析推荐方法所需的专家意见。我们展示了这种方法如何使试验分析充分认识到对缺失数据的原因做出替代的、合理的假设所产生的不确定性。该工具可广泛用于未来试验的设计、分析和解释，为了促进这一点，可下载材料。
The analyses of randomised controlled trials with missing data typically assume that, after conditioning on the observed data, the probability of missing data does not depend on the patient’s outcome, and so the data are ‘missing at random’ . This assumption is usually implausible, for example, because patients in relatively poor health may be more likely to drop out. Methodological guidelines recommend that trials require sensitivity analysis, which is best informed by elicited expert opinion, to assess whether conclusions are robust to alternative assumptions about the missing data. A major barrier to implementing these methods in practice is the lack of relevant practical tools for eliciting expert opinion. We develop a new practical tool for eliciting expert opinion and demonstrate its use for randomised controlled trials with missing data. We develop and illustrate our approach for eliciting expert opinion with the IMPROVE trial (ISRCTN 48334791), an ongoing multi-centre randomised controlled trial which compares an emergency endovascular strategy versus open repair for patients with ruptured abdominal aortic aneurysm. In the IMPROVE trial at 3 months post-randomisation, 21% of surviving patients did not complete health-related quality of life questionnaires (assessed by EQ-5D-3L). We address this problem by developing a web-based tool that provides a practical approach for eliciting expert opinion about quality of life differences between patients with missing versus complete data. We show how this expert opinion can define informative priors within a fully Bayesian framework to perform sensitivity analyses that allow the missing data to depend upon unobserved patient characteristics. A total of 26 experts, of 46 asked to participate, completed the elicitation exercise. The elicited quality of life scores were lower on average for the patients with missing versus complete data, but there was considerable uncertainty in these elicited values. The missing at random analysis found that patients randomised to the emergency endovascular strategy versus open repair had higher average (95% credible interval) quality of life scores of 0.062 (−0.005 to 0.130). Our sensitivity analysis that used the elicited expert information as pooled priors found that the gain in average quality of life for the emergency endovascular strategy versus open repair was 0.076 (−0.054 to 0.198). We provide and exemplify a practical tool for eliciting the expert opinion required by recommended approaches to the sensitivity analyses of randomised controlled trials. We show how this approach allows the trial analysis to fully recognise the uncertainty that arises from making alternative, plausible assumptions about the reasons for missing data. This tool can be widely used in the design, analysis and interpretation of future trials, and to facilitate this, materials are available for download.
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影响因子：
3.7
作者：
HOGARTH, RM
通讯作者：
HOGARTH, RM
影响因子：
2
作者：
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作者：
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作者：
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通讯作者：
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影响因子：
39.3
作者：
Grieve, Richard;Gomes, Manuel;Powell, Janet T.
通讯作者：
Powell, Janet T.