Statistical Methods and Theory for Clinical Trials in the Era of Patient-Oriented Research and Personalized Medicine

以患者为中心的研究和个性化医疗时代临床试验的统计方法和理论

• 批准号: RGPIN-2022-03788
• 负责人: Tu, Dongsheng
• 金额: $ 1.97万
• 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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764374
• 关键词: Statistical; Methods; Theory; Clinical; Trials

The primary objectives of my research program are to lay solid mathematical foundations for statistical methods in the design and analysis of clinical trials for the evaluation of new drugs or procedures in the prevention and treatment of the diseases and, if methods are not available, to develop new statistical methods with a through investigation of their mathematical properties.  In recent years, patient-orientated research and development of personalized medicines are two focus areas in the clinical trials. Patient-orientated research intends to involve patients in the design, conduct, and interpretation of a study including the assessment on the effects of treatments by outcomes reported by patients through answers to questions on specific questionnaires, while personalized medicine aims the development of medical treatment tailored to the individual characteristics of each patient. New statistical methods and theory are required for the design and analysis of clinical trials with these two research focuses.  In the last granting cycle, among other achievements, we have made major contributions in this area of statistical research. 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) Development of a mixture density ratio model and associated inference procedures for the analysis of longitudinal patient reported outcomes which are restricted to a closed interval; (2) Development of statistical methods which can be used to identify subgroups of patients who may benefit from or be harmed by a new treatment with respect to outcomes reported by patients based on continuous and/or multiple biomarkers; (3) Theoretical evaluations of resampling procedures for the assessment of the effects on time to an event outcome for biomarkers which are selected by LASSO and related procedures; (4) Development of statistical procedures for subgroup analyses with multiple biomarkers and time to an event outcomes based on a nonparametric measurement of treatment effects. 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 diseases and, therefore, reduction of morbidity and mortality from these diseases. It is also expected it will stimulate new development in the mathematical theory of probability and statistics. The theory and methods developed from this project may be applied to other types of clinical studies and also other fields of natural science and engineering such as physical and chemical testing with limits of detection and reliability engineering. All levels of Highly Qualified Personnel will be trained through the participation in the projects listed in this proposal.

我的研究计划的主要目标是为临床试验的设计和分析奠定坚实的统计方法数学基础，以评估预防和治疗疾病的新药或程序，如果方法不可用，则通过对其数学性质的调查来开发新的统计方法。以患者为导向的研究和个性化药物的开发是临床试验的两个重点领域。以患者为导向的研究旨在让患者参与研究的设计，实施和解释，包括通过患者通过回答特定问卷上的问题报告的结果评估治疗效果，而个性化医疗旨在根据每个患者的个人特征制定医疗方案。这两个研究重点的临床试验的设计和分析需要新的统计方法和理论。在上一个资助周期中，我们在这一统计研究领域做出了重大贡献。我们计划继续这项研究计划，重点研究我们最近在实践中遇到的以下四个问题：（1）发展一个混合密度比模型和相关的推理程序，用于分析限制在一个封闭区间内的纵向患者报告结果;（2）开发统计方法，根据患者报告的结果，根据连续和/或非连续性数据，或多个生物标志物;（3）用于评估由LASSO和相关程序选择的生物标志物对事件结局时间的影响的恢复程序的理论评价;（4）基于治疗效果的非参数测量，开发用于多个生物标志物和事件结局时间的亚组分析的统计程序。预计这项研究将为从事临床试验和其他相关领域工作的应用统计学家产生一些新的统计工具，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疾病的新战略，从而减少这些疾病的发病率和死亡率。它也将促进概率统计数学理论的新发展。本项目所开发的理论和方法可应用于其他类型的临床研究，也可应用于其他自然科学和工程领域，如具有检测限的物理和化学测试以及可靠性工程。所有级别的高素质人员将通过参与本建议书中所列的项目进行培训。