MULTIVARIATE GROUP SEQUENTIAL CANCER CLINICAL TRIALS

多变量组序贯癌症临床试验

• 批准号: 6173406
• 负责人: MICHAEL R KOSOROK
• 金额: $ 9.66万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2002-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6173406
• 关键词: computer simulation; data collection methodology /evaluation; human data; statistics /biometry

DESCRIPTION: (Adapted from applicant's abstract): For ethical and economic reasons, many Phase III cancer clinical trials incorporate group sequential interim monitoring to permit appropriate early stopping in the presence of a clear treatment effect. Frequently, staggered entry of patients into these studies is an operational necessity which can complicate the distributional properties of the test statistics used. This difficulty is exacerbated when multiple outcome are being considered, especially if one or more of the outcomes is a failure time. However, a number of significant advances in survival analysis theory and implementation over the last several decades have resulted in a rich variety of statistics which can be sensitive to many different alternative hypotheses: but the flexibility and applicability to the group sequential setting is severely limited by the analytic complexity of the underlying distributions. The proposed research will seek to address these issues through the following interrelated goals: (1) Develop flexible Monte Carlo methods for accurately determining the null distribution of multivariate statistical tests in a group sequential clinical trial with staggered entry of patients; (2) Develop versatile survival analysis test procedures possessing improved flexibility, which can be generalized to permit tied data, stratification, and the comparison of more than two treatments; (3) Evaluate and compare these versatile procedures using analytic, data, and simulation studies so that clear criteria for optimal use can be established; (4) Further extend these results for evaluating power and sample size requirements in group sequential designs; (5) Use these Monte Carlo procedures to construct flexible multivariate group sequential boundaries which correspond to hypotheses which are clinically relevant; (6) Develop a suitable method of assessing multivariate information accrual so that the alpha-spending approach for designing sequential clinical trials can be applied to this setting; and (7) Implement these methods in flexible, well documented, and user-friendly software. The theme for this research is increasing appropriate utilization of multiple endpoint data in cancer clinical trials through development of flexible multivariate test statistics in a group sequential setting.

描述：（改编自申请人摘要）：出于伦理和经济原因 由于这些原因，许多III期癌症临床试验将组序贯 临时监测，以便在出现以下情况时适当提前停止 治疗效果明显。 经常，病人交错进入这些 研究是一种业务需要，可能会使分配复杂化， 使用的测试统计量的属性。 这种困难加剧，当 正在考虑多种结果，特别是如果一个或多个 结果是一个失败的时间。 然而，在以下方面取得了一些重大进展： 生存分析理论和实施在过去几十年中 产生了各种各样的统计数据，这些数据可能对许多人很敏感。 不同的替代假设：但灵活性和适用性， 组顺序设置受到分析复杂性的严重限制 底层的分布。 拟议的研究将寻求解决 通过以下相互关联的目标来解决这些问题：（1）制定灵活的 精确确定零分布的蒙特卡罗方法 多变量统计检验在一组序贯临床试验中， （2）发展多功能生存分析测试 具有改进的灵活性的程序，可以推广到 允许并列数据、分层和两个以上的比较 治疗;（3）评估和比较这些通用程序， 分析，数据和模拟研究，以便明确的标准， （4）进一步推广这些结果，以评估 组序贯设计中的功效和样本量要求;（5）使用 这些蒙特卡罗程序构造灵活的多元组 对应于临床假设的连续边界 （6）制定一个适当的方法来评估多变量 信息积累，使阿尔法支出的方法，设计 连续的临床试验可以应用于这种设置;和（7）实施 这些方法在灵活的，有据可查的，用户友好的软件。 的 本研究的主题是提高多个 通过开发灵活的 多变量检验统计在一组序贯设置。