Cambridge Centre for Health Services Research, Institute of Public Health, University of Cambridge, Cambridge, UK.
Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Value Health. 2018 Jun;21(6):669-676. doi: 10.1016/j.jval.2017.10.009. Epub 2017 Dec 8.
Expert elicitation is required to inform decision making when relevant "better quality" data either do not exist or cannot be collected. An example of this is to inform decisions as to whether to screen for melanoma. A key input is the counterfactual, in this case the natural history of melanoma in patients who are undiagnosed and hence untreated.
To elicit expert opinion on the probability of disease progression in patients with melanoma that is undetected and hence untreated.
A bespoke webinar-based expert elicitation protocol was administered to 14 participants in the United Kingdom, Australia, and New Zealand, comprising 12 multinomial questions on the probability of progression from one disease stage to another in the absence of treatment. A modified Connor-Mosimann distribution was fitted to individual responses to each question. Individual responses were pooled using a Monte-Carlo simulation approach. Participants were asked to provide feedback on the process.
A pooled modified Connor-Mosimann distribution was successfully derived from participants' responses. Feedback from participants was generally positive, with 86% willing to take part in such an exercise again. Nevertheless, only 57% of participants felt that this was a valid approach to determine the risk of disease progression. Qualitative feedback reflected some understanding of the need to rely on expert elicitation in the absence of "hard" data.
We successfully elicited and pooled the beliefs of experts in melanoma regarding the probability of disease progression in a format suitable for inclusion in a decision-analytic model.
当相关的“高质量”数据不存在或无法收集时，需要进行专家评估以提供决策依据。例如，这可用于告知是否对黑色素瘤进行筛查的决策。一个关键的输入是反事实情况，在这种情况下，是未经诊断和未经治疗的黑色素瘤患者的自然病史。
评估黑色素瘤患者在未被发现和未经治疗的情况下疾病进展的概率的专家意见。
对来自英国、澳大利亚和新西兰的 14 名参与者进行了一项专门的基于网络研讨会的专家评估方案，该方案包含 12 个关于在未接受治疗的情况下从一种疾病阶段进展到另一种疾病阶段的概率的多项选择问题。对每个问题的个体反应进行了修正的 Connor-Mosimann 分布拟合。使用蒙特卡罗模拟方法对个体反应进行了汇总。要求参与者对过程提供反馈。
从参与者的反应中成功推导出了一个汇总的修正 Connor-Mosimann 分布。参与者的反馈总体上是积极的，86%的人愿意再次参与此类活动。然而，只有 57%的参与者认为这是确定疾病进展风险的有效方法。定性反馈反映了一些人理解在缺乏“硬”数据的情况下需要依赖专家评估的必要性。
我们成功地评估并汇总了黑色素瘤专家对疾病进展概率的意见，以适合纳入决策分析模型的格式。
