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在MISTIC研究的一项小样本n序列、多分配、随机试验(snSMART)中探讨序贯和联合治疗方案。

Addressing sequential and concurrent treatment regimens in a small n sequential, multiple assignment, randomized trial (snSMART) in the MISTIC study.

作者信息

Cheng Yuwei, Tremoulet Adriana, Burns Jane, Jain Sonia

机构信息

Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, USA.

Department of Pediatrics, University of California San Diego, La Jolla, California, USA.

出版信息

J Biopharm Stat. 2025 Jan 2;35(1):106-124. doi: 10.1080/10543406.2023.2292206. Epub 2023 Dec 14.

Abstract

Multisystem Inflammatory Syndrome in children (MIS-C) is a rare and novel pediatric complication linked to COVID-19 exposure, which was first identified in April 2020. A small n, Sequential, Multiple Assignment, Randomized Trial (snSMART) was applied to the Multisystem Inflammatory Syndrome Therapies in Children Comparative Effectiveness Study (MISTIC) to efficiently evaluate multiple competing treatments. In the MISTIC snSMART study, participants are randomized to one of three interventions (steroids, infliximab or anakinra), and potentially re-randomized to the remaining two treatments depending on their response to the first randomized treatment. However, given the novelty and urgency of the MIS-C disease, in addition to patient welfare concerns, treatments were not always administered sequentially, but allowed to be administered concurrently if deemed medically necessary. We propose a pragmatic modification to the original snSMART design to address the analysis of concurrent versus sequential treatments in the MISTIC study. A modified Bayesian joint stage model is developed that can distinguish a concurrent treatment effect from a sequential treatment effect. A simulation study is conducted to demonstrate the improved accuracy and efficiency of the primary aim to estimate the first stage treatments' response rates and the secondary aim to estimate the combined first and second stage treatments' responses in the proposed model compared to the standard snSMART Bayesian joint stage model. We observed that the modified model has improved efficiency in terms of bias and rMSE under large sample size settings.

摘要

儿童多系统炎症综合征(MIS-C)是一种与接触新冠病毒相关的罕见新型儿科并发症,于2020年4月首次被发现。一项小样本、序贯、多重分配、随机试验(snSMART)被应用于儿童多系统炎症综合征治疗比较有效性研究(MISTIC),以有效评估多种相互竞争的治疗方法。在MISTIC的snSMART研究中,参与者被随机分配到三种干预措施之一(类固醇、英夫利昔单抗或阿那白滞素),并可能根据他们对首次随机治疗的反应重新随机分配到其余两种治疗方法。然而,鉴于MIS-C疾病的新颖性和紧迫性,除了对患者福利的担忧外,治疗并非总是按顺序进行,如果认为有医学必要,也允许同时进行。我们提议对原始的snSMART设计进行务实修改,以解决MISTIC研究中同时治疗与序贯治疗的分析问题。开发了一种改进的贝叶斯联合阶段模型,该模型可以区分同时治疗效果和序贯治疗效果。进行了一项模拟研究,以证明与标准的snSMART贝叶斯联合阶段模型相比,所提出的模型在估计第一阶段治疗反应率的主要目标和估计第一阶段和第二阶段联合治疗反应的次要目标方面,提高了准确性和效率。我们观察到,在大样本量设置下,修改后的模型在偏差和均方根误差方面提高了效率。

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Contemp Clin Trials Commun. 2023 Apr;32:101060. doi: 10.1016/j.conctc.2023.101060. Epub 2023 Jan 20.
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