远程双变量专家 elicitation 确定样本量计算的先验概率分布用于贝叶斯非劣性多中心随机对照试验（百日咳给药试验）
Remote, bivariate expert elicitation to determine the prior probability distribution for sample size calculation in a Bayesian non-inferiority multicenter randomized controlled trial (Croup Dosing Trial)
AI总结：
本文通过远程双变量专家 elicitation 方法确定样本量计算的先验分布，用于评估百日咳治疗中不同剂量地塞米松的非劣性，结合专家意见和现有文献，生成了样本量为1850的方案。
摘要：
在贝叶斯临床试验中，必须为感兴趣的参数指定先验分布。当现有证据有限时，可通过专家 elicitation 构建先验分布。然而，传统 elicitation 需要面对面交流和预 elicitation 培训，这可能不可行。我们的远程 elicitation 基于已建立的专家 elicitation 方法。我们使用双变量先验分布来处理 elicited 量之间的依赖性。我们 elicited 了用于评估7天内儿童百日咳就诊次数的先验分布。该试验评估了0.15 mg/kg地塞米松与标准剂量0.60 mg/kg在治疗百日咳中的非劣性。我们进行了三次远程研讨会，以 elicite 专家对两种地塞米松剂量疗效的看法。每次研讨会包括两次调查轮次，中间有小组讨论。在研讨会前，专家回顾了提供的关于两种地塞米松剂量效果的文献。信念通过专家特定的双变量分布进行汇总。汇总的分布和调查的非劣性边际确定了样本量。12名急诊医学医生参与了我们的远程 elicitation 活动。elicitation 生成了一个以0.60 mg/kg剂量为中心为6%、0.15 mg/kg剂量为中心为8%的先验分布。汇总的先验分布产生了基于非劣性边际为4%的样本量1850。我们 elicited 的先验分布结合了过去证据和专家意见。 elicited 的先验与关于地塞米松剂量治疗百日咳效果的文献一致。我们的方法展示了远程 elicitation 双变量分布用于临床试验的可行性。
英文摘要：
Prior distributions must be specified for the parameters of interest in a Bayesian clinical trial. When existing evidence on the effects of the trial interventions is limited, prior distributions can be constructed with expert elicitation. However, conventional elicitation requires face-to-face interactions and intensive pre-elicitation training, which can be infeasible. Our remote elicitation was based on established expert elicitation methods. We used bivariate prior distributions for dependencies between elicited quantities. We elicited a prior distribution for the Croup Dosing Trial, which will assess the number of return visits to the emergency department within 7 days in children with croup. This trial evaluates the non-inferiority of 0.15 mg/kg of dexamethasone, compared to the standard dose of 0.60 mg/kg to treat croup. We conducted three remote workshops to elicit expert beliefs on the efficacy of the two doses of dexamethasone. Each workshop consisted of two survey rounds, separated by a group discussion. Prior to the workshop, experts reviewed provided literature on the effects of the two doses of dexamethasone. Beliefs were aggregated with expert-specific bivariate distributions. The aggregated distribution and surveyed non-inferiority margin determined the sample size. Twelve emergency medicine physicians participated in our remote elicitation exercise. The elicitation generated a prior distribution centered at 6% for the 0.60 mg/kg dose and 8% for the 0.15 mg/kg dose. The aggregated prior distribution produced a sample size of 1850, based on a non-inferiority margin of 4%. We elicited a prior distribution that incorporated past evidence and expert opinion. The elicited prior is consistent with literature on the efficacy of the dexamethasone doses in treating croup. Our approach demonstrates the feasibility of remotely eliciting bivariate distributions for clinical trials.
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