Dose and Treatment Selection in Clinical Trials

临床试验中的剂量和治疗选择

基本信息

  • 批准号:
    7895918
  • 负责人:
  • 金额:
    $ 35.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-07-08 至 2013-06-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Clinical trials of a new treatment may proceed through three phases. Phase I trials are small studies that evaluate toxicity with a specific task to determine the maximum tolerated dose. Once a safe dose of the treatment is chosen, its therapeutic efficacy will be tested in a phase II trial. Regimens shown promising in phase II trials will then be moved to large, multi-institutional phase III studies that compare their effectiveness to standard treatments. With many candidate regimens available, it is imperative to identify the most promising therapies for the expensive phase III testing. This has become increasingly important because of the limited subject availability and funding resources, and an ever increasing number of new compounds due to high throughput screening. In this research, we propose novel statistical designs and strategies that utilize the complex clinical data in an efficient manner, which is hoped to translate into equally accurate clinical conclusions with fewer resources. Specifically, this renewal application covers the following three clinical scenarios. First, we propose methods for phase I dose-finding trials with multiple safety endpoints under heteroscedasticity and multiple objective constraints. Existing designs collapse the endpoints into a dichotomized indicator of toxicity or no-toxicity, and may do so at the expense of not utilizing all information available and over-simplifying the complex clinical objectives. Our proposed methods will retrieve the information loss by using all endpoints and achieve clinical relevance by accommodating multiple objective constraints. Second, we propose methods for phase II dose- finding trials based on both safety and efficacy endpoints, in which patients will be enrolled in two stages. Having an interim analysis, we can shut down ineffective or unsafe doses and reduce the number of patients treated at these doses. Third, we propose designs to select treatments in phase II trials based on both clinical and biologic endpoints. This work extends our ongoing research on sequential selection boundaries for trials with a single biologic endpoint. While a biologic endpoint is typically less noisy than a clinical endpoint such as the modified Rankin scale in stroke patients, the primary therapeutic objective is to improve the clinical outcomes. Our bivariate approach will improve the efficiency in treatment selection by using the less noisy biologic endpoint while assuring the design is clinically relevant via its use of the clinical outcomes. These designs will be applied to design various clinical trials in patients with neurological disorders. PUBLIC HEALTH RELEVANCE: Despite the efforts in the past decade, additional therapies for neurological disorders such as acute ischemic stroke are sorely needed. Upon successful completion of this research, we will extend our capacity to design early phase investigation of new treatments and enhance the statistical efficiency of selection and screening process in a variety of clinical trial settings.
描述(由申请人提供):新疗法的临床试验可分为三个阶段。一期试验是小型研究,通过特定任务评估毒性,以确定最大耐受剂量。一旦选择了安全的治疗剂量,其治疗效果将在II期试验中进行测试。在II期试验中表现出希望的方案将随后转移到大型、多机构的III期研究,将其与标准治疗的效果进行比较。由于有许多候选方案可供选择,因此必须为昂贵的III期试验确定最有希望的治疗方法。由于有限的受试者可用性和资金资源,以及由于高通量筛选而不断增加的新化合物,这一点变得越来越重要。在这项研究中,我们提出了新的统计设计和策略,以有效的方式利用复杂的临床数据,希望以更少的资源转化为同样准确的临床结论。具体来说,此续期申请涵盖以下三种临床情况。首先,我们提出了在异方差和多目标约束下具有多个安全终点的I期剂量寻找试验方法。现有的设计将终点分解为毒性或无毒性的二分类指标,这样做可能会以不利用所有可用信息和过度简化复杂的临床目标为代价。我们提出的方法将通过使用所有端点来检索信息丢失,并通过适应多个目标约束来实现临床相关性。其次,我们提出了基于安全性和有效性终点的II期剂量寻找试验方法,其中患者将分为两个阶段。通过中期分析,我们可以关闭无效或不安全的剂量,并减少用这些剂量治疗的患者人数。第三,我们建议在基于临床和生物学终点的II期试验中选择治疗方案。这项工作扩展了我们正在进行的关于单一生物终点试验的顺序选择边界的研究。虽然生物学终点通常比临床终点(如卒中患者的改良Rankin量表)噪音小,但主要的治疗目标是改善临床结果。我们的双变量方法将通过使用较少噪声的生物终点来提高治疗选择的效率,同时通过使用临床结果来确保设计与临床相关。这些设计将应用于设计各种神经系统疾病患者的临床试验。公共卫生相关性:尽管在过去十年中做出了努力,但迫切需要对急性缺血性中风等神经系统疾病进行额外的治疗。在成功完成这项研究后,我们将扩大我们的能力来设计新疗法的早期研究,并提高在各种临床试验环境中选择和筛选过程的统计效率。

项目成果

期刊论文数量(14)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Calibration of prior variance in the Bayesian continual reassessment method.
  • DOI:
    10.1002/sim.4139
  • 发表时间:
    2011-07-30
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Lee, Shing M.;Cheung, Ying Kuen
  • 通讯作者:
    Cheung, Ying Kuen
Model calibration in the continual reassessment method.
  • DOI:
    10.1177/1740774509105076
  • 发表时间:
    2009-06
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Lee SM;Ying Kuen Cheung
  • 通讯作者:
    Ying Kuen Cheung
Selecting promising treatments in randomized Phase II cancer trials with an active control.
在具有主动对照的随机 II 期癌症试验中选择有希望的治疗方法。
A note on confidence bounds after fixed-sequence multiple tests.
关于固定序列多重测试后置信界限的注释。
Stochastic approximation with virtual observations for dose-finding on discrete levels.
具有虚拟观察的随机近似,用于离散水平上的剂量查找。
  • DOI:
    10.1093/biomet/asp065
  • 发表时间:
    2010
  • 期刊:
  • 影响因子:
    2.7
  • 作者:
    Cheung,YingKuen;Elkind,MitchellSV
  • 通讯作者:
    Elkind,MitchellSV
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Ken Cheung其他文献

Ken Cheung的其他文献

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{{ truncateString('Ken Cheung', 18)}}的其他基金

Breaking up Prolonged Sedentary Behavior to Improve Cardiometabolic Health: An Adaptive Dose-Finding Study
打破长时间久坐行为以改善心脏代谢健康:一项适应性剂量探索研究
  • 批准号:
    10667379
  • 财政年份:
    2021
  • 资助金额:
    $ 35.99万
  • 项目类别:
Breaking up Prolonged Sedentary Behavior to Improve Cardiometabolic Health: An Adaptive Dose-Finding Study
打破长时间久坐行为以改善心脏代谢健康:一项适应性剂量探索研究
  • 批准号:
    10401933
  • 财政年份:
    2021
  • 资助金额:
    $ 35.99万
  • 项目类别:
Breaking up Prolonged Sedentary Behavior to Improve Cardiometabolic Health: An Adaptive Dose-Finding Study
打破长时间久坐行为以改善心脏代谢健康:一项适应性剂量探索研究
  • 批准号:
    10211145
  • 财政年份:
    2021
  • 资助金额:
    $ 35.99万
  • 项目类别:
Novel Methods for Evaluation and Implementation of Behavioral Intervention Technologies for Depression
抑郁症行为干预技术评估和实施的新方法
  • 批准号:
    9083697
  • 财政年份:
    2016
  • 资助金额:
    $ 35.99万
  • 项目类别:
Physical Activity Patterns via New Dimension-Informative Cluster Models.
通过新维度信息集群模型的身体活动模式。
  • 批准号:
    8532031
  • 财政年份:
    2012
  • 资助金额:
    $ 35.99万
  • 项目类别:
Physical Activity Patterns via New Dimension-Informative Cluster Models.
通过新维度信息集群模型的身体活动模式。
  • 批准号:
    8369662
  • 财政年份:
    2012
  • 资助金额:
    $ 35.99万
  • 项目类别:
Physical Activity Patterns via New Dimension-Informative Cluster Models.
通过新维度信息集群模型的身体活动模式。
  • 批准号:
    8657101
  • 财政年份:
    2012
  • 资助金额:
    $ 35.99万
  • 项目类别:
Physical Activity Patterns via New Dimension-Informative Cluster Models.
通过新维度信息集群模型的身体活动模式。
  • 批准号:
    8839813
  • 财政年份:
    2012
  • 资助金额:
    $ 35.99万
  • 项目类别:
Developing Optimal Dynamic Behavioral Intervention in Community-Based Studies.
在基于社区的研究中制定最佳动态行为干预。
  • 批准号:
    8462308
  • 财政年份:
    2011
  • 资助金额:
    $ 35.99万
  • 项目类别:
Developing Optimal Dynamic Behavioral Intervention in Community-Based Studies.
在基于社区的研究中制定最佳动态行为干预。
  • 批准号:
    8269641
  • 财政年份:
    2011
  • 资助金额:
    $ 35.99万
  • 项目类别:

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