Empirical Likelihood Bayes Analysis of Quantile Regression Model

分位数回归模型的经验似然贝叶斯分析

• 批准号: 7878737
• 负责人: Mi-Ok Kim
• 金额: $ 7.9万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2011-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7878737
• 关键词: Accounting; Acute Lymphocytic Leukemia; Address; Adult; Affect; Age; Autologous Bone Marrow Transplantation; Bayesian Method; Body mass index; Cancer Patient; Cancer Survivor; Cancer and Leukemia Group B; Cephalic; Childhood Acute Lymphocytic Leukemia; Childhood Cancer Survivor Study; Cohort Studies; Computational algorithm; Computer software; Data; Data Analyses; Diagnosis; Disease; Disease-Free Survival; Dose; Environmental Risk Factor; Future; Gender; Generic Drugs; Genetic; Hand; Health; High Dose Chemotherapy; High-Risk Cancer; Intervention; Knowledge; Lead; Malignant Childhood Neoplasm; Methodology; Methods; Modeling; Morbidity - disease rate; Obesity; Overweight; Patients; Predisposition; Radiation therapy; Randomized Clinical Trials; Regression Analysis; Relative (related person); Research; Research Design; Risk; Risk Factors; Role; Siblings; Survivors; Testing; Time; Treatment Protocols; Woman; base; cancer epidemiology; cancer therapy; chemotherapy; childhood cancer survivor; design; epidemiology study; falls; hazard; high risk; improved; innovation; malignant breast neoplasm; mortality; obesity risk; outcome forecast; patient population; prospective; public health relevance; software development; tool; treatment effect; trial comparing

DESCRIPTION (provided by applicant): The purpose of this study is reanalyzing the Childhood Cancer Survivors Study (CCSS) and the Cancer and Leukemia Group B (CALGB) study 9082 data using an innovative Bayesian method for quantile regression (QR) and censored QR model. The CCSS and the CALGB study 9082 are concerned with two important questions of cancer epidemiology, respectively, identifying and assessing risk factors for modifiable disease and weighing more aggressive cancer treatment against less aggressive one. The primary analyses of the studies were constrained by the study design or the choice of statistical analysis method and fell short of adequately answering their respective research questions. Reanalyzing these studies is well warranted by appropriately addressing such constraints. We will use an innovative Bayesian (censored) QR method. It replaces the likelihood with empirical likelihood within the Bayesian analytic framework and conducts (censored) QR analysis. It will be a method, the first and only regarding the censored QR and one among a few regarding the uncensored QR, that accommodate all the features that are essential to adequately reanalyze the CCSS and the CALGB study 9082 data. It will also provide an alternative analytic tool for many other cancer epidemiology studies where standard regression or survival data analysis methods fail or are deemed insufficient. This study will improve our understanding of, respectively, obesity related future health risks in the childhood acute lymphoblastic leukemia (ALL) survivors and the role of cranial radiotherapy, and of the relative benefit of the high dose chemotherapy (with autologous bone marrow transplantation) in women with high risk breast cancer. This knowledge will consequently lead to better designed treatment protocols and intervention strategies that will increase survival and minimize harmful health effects in pediatric cancer and high risk breast cancer patient populations. PUBLIC HEALTH RELEVANCE: The purpose of this study is reanalyzing the Childhood Cancer Survivors Study (CCSS) and the Cancer and Leukemia Group B (CALGB) study 9082 by using an innovative Bayesian method for quantile regression and censored quantile regression model. The proposed analyses will improve our understanding of, respectively, obesity related future health risks in the childhood acute lymphoblastic leukemia (ALL) survivors and the role of cranial radiotherapy, and of the relative benefit of high dose chemotherapy with autologous bone marrow transplantation in women with high risk breast cancer.

描述（由申请人提供）： 本研究的目的是重新分析儿童癌症幸存者研究（CCSS）和癌症和白血病组B（CALGB）研究9082数据使用一种创新的贝叶斯方法的分位数回归（QR）和删失QR模型。CCSS和CALGB研究9082分别关注癌症流行病学的两个重要问题，即识别和评估可改变疾病的风险因素，以及权衡更积极的癌症治疗与不那么积极的癌症治疗。研究的主要分析受到研究设计或统计分析方法选择的限制，无法充分回答各自的研究问题。重新分析这些研究是很有必要的，适当解决这些限制。我们将使用创新的贝叶斯（删失）QR方法。它在贝叶斯分析框架内用经验似然代替似然，并进行（删失）QR分析。这将是一种方法，第一种也是唯一一种关于删失QR的方法，也是少数几种关于未删失QR的方法之一，它包含了充分重新分析CCSS和CALGB研究9082数据所必需的所有特征。它还将为许多其他癌症流行病学研究提供替代分析工具，其中标准回归或生存数据分析方法失败或被认为是不够的。这项研究将提高我们对儿童急性淋巴细胞白血病（ALL）幸存者肥胖相关的未来健康风险和颅放射治疗的作用的理解，以及高剂量化疗（自体骨髓移植）在高危乳腺癌女性中的相对获益。因此，这些知识将导致更好地设计治疗方案和干预策略，从而提高儿童癌症和高危乳腺癌患者群体的生存率并最大限度地减少有害健康影响。 公共卫生相关性： 本研究的目的是重新分析儿童癌症幸存者研究（CCSS）和癌症和白血病组B（CALGB）研究9082，使用一种创新的贝叶斯分位数回归方法和删失分位数回归模型。建议的分析将分别提高我们对儿童急性淋巴细胞白血病（ALL）幸存者肥胖相关的未来健康风险和颅放射治疗的作用的理解，以及高剂量化疗联合自体骨髓移植在高危乳腺癌女性中的相对获益。