Statistical Methods for Cancer Clinical Trials

癌症临床试验的统计方法

• 批准号: 8794722
• 负责人: MARIE DAVIDIAN
• 金额: $ 197.69万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8794722
• 关键词: Address; Adopted; Adoption; Advanced Malignant Neoplasm; Algorithms; Animals; Biological Markers; Cancer Patient; Characteristics; Clinical Research; Clinical Sciences; Clinical Trials; Clinical Trials Design; Communication; Computational Science; Computer software; Conduct Clinical Trials; Data; Data Analyses; Decision Making; Development; Educational workshop; Evaluation; Event; Fostering; Future; Genomics; Goals; Health; Human; Individual; Institution; Lead; Malignant Neoplasms; Malignant neoplasm of pancreas; Medicine; Methodology; Methods; Molecular; Outcome; Patient Outcomes Assessments; Patients; Personal Satisfaction; Persons; Pharmacogenomics; Phase; Phase II Clinical Trials; Pilot Projects; Play; Pre-Clinical Model; Probability; Process; Public Health; Research; Research Personnel; Research Project Grants; Resource Sharing; Resources; Role; Sample Size; Science; Statistical Methods; Time; Toxic effect; Translating; Translations; Validation; anticancer research; base; cancer therapy; candidate marker; clinical practice; design; effectiveness clinical trial; exome sequencing; forging; improved; innovation; neoplastic cell; novel; outreach; personalized cancer therapy; personalized medicine; pilot trial; pre-clinical; preclinical study; prognostic; programs; success; symposium; tool; treatment response; treatment strategy; trial design; tumor; user friendly software; web site

DESCRIPTION (provided by applicant): The overarching goal of this ambitious program project continues to be to develop innovative, transformative statistical methods for cancer clinical trials that have the potential to hasten successful introduction of new therapies and treatment strategies into practice. Advances in the biologic, genomic, statistical, and computational sciences hold great promise for the development of personalized cancer treatments. Our multi-institutional, interdisciplinary team of investigators will leverage these advances to create new clinical trial designs and data analysis approaches that resolve many of the key limitations of current statistical methods and that maximize the effectiveness of clinical trials for personalized cancer medicine. In addition, we will foster translation of these methods into practice, including carrying out pilot animal and human studies based on the new methodology. The program will achieve these objectives through five, interrelated research projects carried out by investigators with complementary expertise in the statistical, computational, and clinical sciences from three institutions. The first four projects focus on developing new trial designs and analysis methods that integrate biomarkers for efficient discovery of new, personalized treatments; on creating methods for analysis of existing data on biomarkers and patient reported outcomes to inform and improve the design of future studies; developing methods for maximizing the power of pharmacogenomics for identifying biomarkers and candidate individualized therapies; and creating new methods for discovering and validating sequential, personalized decision-making strategies for cancer treatment. The fifth project will integrate the methods into novel preclinical and clinical studies of pancreatic cancer. Our comprehensive approach involves an energetic and coordinated process for implementation, communication, and dissemination of results, including development of professional, public-use software and associated tutorials; workshops and other outreach mechanisms; and program-sponsored symposia and events, to accelerate the adoption of the methods in practice. The proposed clinical trial design and analysis innovations have the potential to effect a paradigm shift in the way cancer clinical trials are conducted for discovery and validation of personalized medicine. This comprehensive, multi-institutional effort will lead to significant innovations in cancer clinical trial practice that will result in improved health of cancer patients.

描述（由申请人提供）：这个雄心勃勃的计划项目的总体目标继续是为癌症临床试验开发创新的，变革性的统计方法，这些方法有可能成功将新的疗法和治疗策略促进实践。生物学，基因组，统计和计算科学的进步对发展个性化癌症治疗的发展有很大的希望。我们的多机构跨学科研究人员将利用这些进步来创建新的临床试验设计和数据分析方法，以解决当前统计方法的许多关键局限性，并最大程度地提高个性化癌症医学的临床试验的有效性。此外，我们还将将这些方法的翻译促进实践，包括基于新方法进行试点动物和人类研究。该计划将通过五个相互关联的研究项目实现这些目标，该项目由来自三个机构的统计，计算和临床科学方面的互补专业知识进行。前四个项目着重于开发新的试验设计和分析方法，以有效地发现新的个性化治疗方法，以整合生物标志物；关于分析生物标志物和患者报告的现有数据的方法，以告知和改善未来研究的设计；开发用于最大化药物基因组学能力来鉴定生物标志物和候选个性化疗法的方法；并创建新方法，以发现和验证癌症治疗的顺序，个性化的决策策略。第五个项目将将方法整合到胰腺癌的新临床前和临床研究中。我们的全面方法涉及实施，沟通和结果的充满活力和协调的过程，包括开发专业，公共用途软件和相关教程；研讨会和其他外展机制；以及计划赞助的研讨会和事件，以加速实践中的方法。提出的临床试验设计和分析创新有可能影响癌症临床试验的范式转变，以发现和验证个性化医学。这项全面的多机构努力将导致癌症临床试验实践的重大创新，从而改善癌症患者的健康状况。