Topics in Statistical Theory and Methods for Cancer Clinical Trials

癌症临床试验统计理论与方法专题

• 批准号: RGPIN-2016-04819
• 负责人: Tu, Dongsheng
• 金额: $ 2.4万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709285
• 关键词: Topics; Statistical; Theory; Methods; Cancer

Cancer is a major public health problem in Canada and around the world. Research on the cause, detection, prevention and treatment of cancer is one of the most active research areas in the health sciences. Clinical trials are key component in the development of new drugs or procedures to treat the cancer or prevent the development of the cancer. Statistical methods play a pivotal role in the design and analysis of cancer clinical trials. Because of rapid progress in the understanding of cancer biology, many new drugs and treatment procedures have been developed in the recent years. New statistical methods are required to make the clinical trials evaluating these drugs and procedures more accurate and efficient. Development and evaluation of these new statistical methods with applications to the clinical trials conducted by the NCIC Clinical Trials Group has been the primary topic of our research program. We plan to continue this research program with focus on the study of the following four problems we have encountered recently in our practices: (1) Statistical inference of two-stage phase II cancer clinical trials with correlated endpoints; (2) Statistical inference procedures for an alternative measure of treatment effect based on paired survival data; (3) Statistical procedures for the analysis of survival outcomes from covariate-adaptive designs; (4) Statistical methods for the identification of predictive signatures from multiple and correlated biomarkers. It is expected that this research will generate some new statistical tools for applied statisticians working in clinical trials and other related areas and also lay solid mathematical foundations for these new methods, which will result in more efficient and reliable identification of new strategies for the prevention and treatment of cancer and, therefore, reduction of morbidity and mortality from cancer. It is also expected this research will stimulate new development in the mathematical theory of probability and statistics. The theory and methods developed from this project may be applied to the evaluation of treatment for other diseases and also other fields of natural science and engineering. All levels of Highly Qualified Personnel will be trained through the participation in the projects listed in this proposal.

癌症是加拿大和世界各地的一个主要公共卫生问题。关于癌症的病因、检测、预防和治疗的研究是健康科学中最活跃的研究领域之一。临床试验是开发治疗癌症或预防癌症发展的新药或程序的关键组成部分。统计学方法在癌症临床试验的设计和分析中起着至关重要的作用。近年来，由于对癌症生物学认识的快速发展，许多新的药物和治疗方法被开发出来。需要新的统计方法来使评估这些药物和程序的临床试验更加准确和高效。 开发和评估这些新的统计方法，并将其应用于NCIC临床试验小组进行的临床试验，一直是我们研究计划的主要主题。我们计划继续这一研究计划，重点研究我们最近在实践中遇到的以下四个问题： (1)终点相关的两期癌症临床试验的统计推断； (2)基于配对生存数据的治疗效果替代措施的统计推断程序； (3)协变量适应性设计的生存结果分析的统计程序； (4)从多个相互关联的生物标志物中识别预测特征的统计方法。 预计这项研究将为在临床试验和其他相关领域工作的应用统计学家提供一些新的统计工具，并为这些新方法奠定坚实的数学基础，从而更有效和可靠地确定预防和治疗癌症的新战略，从而减少癌症的发病率和死亡率。预计这项研究将促进概率统计数学理论的新发展。本项目发展的理论和方法可应用于其他疾病的治疗评价，也可应用于自然科学和工程的其他领域。将通过参与本提案所列项目，培训各级高素质人员。