Design and Analysis of Basket and Umbrella Trials

篮式和伞式试验的设计与分析

• 批准号: 2284124
• 金额: --
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2284124
• 关键词: Design; Analysis; Basket; Umbrella; Trials

Prior to treatments' release onto the market, they undergo rigorous testing in clinical trials. Patients responses to such treatments can vary based on their intrinsic factors, and thus it is desirable to target treatments to patient's presenting different characteristics. To address this issue, so-called basket and umbrella trials are proposed. Basket trials consist of a single treatment applied to different patient groups who share a common characteristic but suffer from different diseases. Umbrella trials are composed of multiple treatments tested in parallel on patients who share the same disease but present a different genetic make-up. We must also consider that, although the primary goal of a trial is to identify the most effective treatment, a secondary goal is to deliver the best treatment to patients within the trial. This is achieved through response-adaptive randomisation, a technique that alters the chance of being allocated a treatment on the basis of data from previously treated patients within the trial. STOR-i and Roche have collaborated to create a project that aims to answer the following questions: How do we borrow information between treatment groups in basket trials? How can we utilize response-adaptive randomisation to improve the number of patients benefiting from the trial? And finally, how can we change the study populations of sub-studies within umbrella trials in order to incorporate newly identified targeted treatments? To tackle these problems, we first focus in on borrowing information between sub-studies and how to efficiently add a sub-group to a basket trial within this borrowing structure. Adding a sub-group is a highly beneficial feature of the aforementioned trial designs, as a new patient population may be identified part way through the trial. Following this, we will explore the operating characteristics of response-adaptive randomisation and how it is impacted on by temporal changes in the disease or health care provision. In partnership with Roche.

在治疗药物投放市场之前，它们要经过严格的临床试验测试。患者对这种治疗的反应可以基于其内在因素而变化，因此期望将治疗靶向于呈现不同特征的患者。为了解决这个问题，提出了所谓的篮子和伞试验。篮子试验包括应用于具有共同特征但患有不同疾病的不同患者群体的单一治疗。伞式试验由多种治疗组成，这些治疗对患有相同疾病但遗传组成不同的患者进行平行测试。 我们还必须考虑到，尽管试验的主要目标是确定最有效的治疗方法，但次要目标是为试验中的患者提供最佳治疗。这是通过反应适应性随机化来实现的，这种技术根据试验中既往接受过治疗的患者的数据来改变分配治疗的机会。 STOR-i和罗氏合作创建了一个项目，旨在回答以下问题：在篮子试验中，我们如何在治疗组之间借用信息？我们如何利用反应适应性随机化来增加从试验中获益的患者数量？最后，我们如何改变伞形试验中的子研究的研究人群，以纳入新确定的靶向治疗？为了解决这些问题，我们首先关注子研究之间的借用信息，以及如何在此借用结构中有效地将子组添加到篮子试验中。增加一个亚组是上述试验设计的一个非常有益的特征，因为新的患者人群可能在试验的中途被识别出来。在此之后，我们将探讨反应自适应随机化的操作特点，以及它如何受到疾病或医疗保健提供的时间变化的影响。与Roche合作。