Training Program in Biostatistics for Cancer Research

描述(由申请者提供)：本申请是为了继续生物统计学方面的培训计划，重点是癌症研究。这个培训项目每年资助六名学生。生物统计学的做法正在发生变化，特别是在癌症领域 研究。在过去的二十年里，对细胞生长和发育的分子、生化和遗传成分的发现改变了我们对是什么使正常细胞癌变，然后转移的理解。鉴于许多癌症的现有治疗方法不胜枚举，每种疗法都对部分患者有效，这些信息有可能被用于个性化治疗，以便每个患者都能得到最有可能受益的治疗，因为他们的癌症的分子特征。早期发现和预防工作也已在许多癌症中取得进展，并显示出降低癌症死亡率和发病率的持续前景。从分子和基因角度研究肿瘤的新方法的发展导致了巨大而复杂的数据集，其相关的生物信息很难提取，其中许多方法的复杂性和超高灵敏度给设计获得可重复测量和可复制结果的研究带来了相当大的挑战。设计能够结合这些信息并将其考虑到患者治疗中的临床试验是具有挑战性的，并且需要仔细处理许多量化问题。多学科研究团队是抗击癌症的现代方法的核心，鉴于许多现代生物医学研究挑战的基本量化性质，生物统计学家和其他量化科学家发现自己在这些团队中越来越重要。这种团队合作要求统计学家熟悉分子生物学家、病理学家，当然还有临床肿瘤学家，如果合作调查组要成功的话。因此，有效的生物统计协作需要在统计学、概率、计算方法以及癌症生物学和医学伦理方面进行广泛的培训。统计系、莱斯大学和德克萨斯大学安德森癌症中心定量科学部的部门与他们在临床和基础科学方面的合作伙伴共同开发了一个独特的培训计划，将各自的优势结合在一起，培训癌症研究方面的生物统计学家。这个生物统计学培训项目的目标是 培养新一代的生物统计学家，他们将在现代癌症研究中与生物医学研究人员并肩工作。我们的计划旨在为学员提供：-统计学和概率方面的严格培训；-基础和临床癌症研究的实践经验；-癌症生物学方面的培训和医学研究伦理。这个项目的学生遵循莱斯大学统计系博士生的标准学习课程，另外还有生物统计学、生物学和伦理学的课程，以及在这两个机构举行的特别研讨会和工作坊。凭借在贝叶斯方法、决策理论、癌症临床试验、癌症筛查、生存分析、统计遗传学、基因组学、生物信息学和统计计算方面的教师专业知识，学员将获得现代癌症研究所需的广泛的生物统计学背景。暑期实习和实验室轮换为学生的培训提供了实践经验。

DESCRIPTION (provided by applicant): This application is for continuation of a training program in biostatistics with a specific focus on cancer research. This training program supports six students each year. The practice of biostatistics is changing, especially in the area of cancer research. Discoveries over the past two decades into the molecular, biochemical, and genetic components of cell growth and development have changed our understanding of what makes a normal cell become cancerous, and then later metastasize. Given numerous available treatments for many cancers, each with efficacy for a subset of patients, this information has the potential to be leveraged to personalize therapy so each patient can be given the treatment that is most likely to benefit them given their cancer's molecular signature. Early detection and prevention efforts have also made inroads in numerous cancers, and demonstrate continuing promise to reduce mortality and morbidity due to cancer. The development of new methods for surveying a tumor molecularly and genetically have led to enormous, complex data sets whose relevant biological information is difficult to extract, and the intricacy and exceeding sensi- tivty of many of these methods raise considerable challenges in terms of designing studies that obtain reproducible measurements and replicable results. Designing clinical trials that can incorporate such information and take it into account in patient treatment is challenging, and requires many quantitative issues be carefully handled. Multidisciplinary research teams are at the heart of modern approaches to fighting cancer, and biostatisticians and other quantitative scientists find themselves as an increasingly crucial part of such teams, given the fundamental quantitative nature of many of the modern biomedical research challenges. Such teamwork requires that the statistician be conversant with molecular biologists, pathologists, and, of course, clinical oncologists if the group of co-investigators is to succeed. Effective biostatisticl collaboration thus requires broad training in statistics, probability, computational methods, as well as cancer biology and medical ethics. The Department of Statistics, Rice University, and the departments in the Division of Quantitative Sciences at the University of Texas M. D. Anderson Cancer Center have joined forces with their collaborators in the clinical and basic sciences to developed a unique training program that combines their respective strengths to train biostatisticians in cancer research. The goal of this Training Program in Biostatistics is to prepare a new generation of biostatisticians who will work side-by-side with biomedical investigators in modern cancer research. Our program aims to provide trainees with: - Rigorous training in statistics and probability; - Practical experience in basic and clinical cancer research; - Training in biological aspects of cancer and medical research ethics. Students in this program follow a standard course of study expected of Ph.D. students in the Department of Statistics at Rice, with additional coursework in biostatistics, biology, and ethics, as well as special seminars and workshops at both institutions. With faculty expertise in Bayesian methods, decision theory, cancer clinical trials, cancer screening, survival analysis, statistical genetics, genomics, bioinformatics, and statistical computing, trainees will receive a broad background in biostatistics necessary for modem cancer research. Summer internships and laboratory rotations provide practical experience in the student's training.