Development and Evaluation of Accelerated Hazards Mixture Cure Model

加速危险混合物固化模型的开发和评估

• 批准号: 7741785
• 负责人: Jiajia Zhang
• 金额: $ 7.26万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7741785
• 关键词: Algorithms; Area; Cancer Patient; Computer software; Data; Data Analyses; Data Set; Development; Disease; Environment; Epidemiologic Studies; Epidemiologist; Evaluation; Failure; Goals; Hazard Models; Long-Term Survivors; Malignant Neoplasms; Medical Research; Methodology; Methods; Modeling; National Cancer Institute; New Jersey; Patients; Performance; Probability; Proportional Hazards Models; Public Health; Relapse; Research Personnel; Risk; Risk Factors; SEER Program; Staging; Survival Rate; Testing; Time; abstracting; anticancer research; base; cancer epidemiology; epidemiology study; hazard; malignant breast neoplasm; models and simulation; public health relevance; simulation; software development; tool; user friendly software

DESCRIPTION (provided by applicant): Abstract : With the advances in cancer research, more and more cancer patients are cured, and they will not relapse or die due to the cancer. It becomes increasingly important to know a patient's chance of being cured given a set of risk factors of the patient, or the survival rate at a certain time if the patient is not cured. The primary aim of this project is to develop a new and 0exible mixture cure model for estimating the proportion of cured patients, and the survival probability of uncured patients. Current methodologies in this area assume that the treatment is e(R)ective at the early stage of trials, while the new model can allow the treatment to have no e(R)ect at the initial time and a gradual e(R)ect later on for uncured patients. This distinctive feature makes the proposed model an important alternative model for practitioners or researchers involved in cancer epidemiology studies in modeling censored survival data with long term survivors. We will develop a semiparametric estimation method, compare it with existing models and methods, evaluate all models by the simulation study, and apply the model to breast cancer data sets. The study will provide practitioners an important tool in analyzing the cancer data with cured fraction and evaluating the risk e(R)ects. The development of the software in the R environment will enable the possible use of the mixture cure model in the epidemiology cancer study easily. PUBLIC HEALTH RELEVANCE: Narrative With the advances in cancer research, more and more cancer patients are cured. This project will investigate a new model for analyzing the cancer survival data with cured patients. The software development in R environment will enable the proposed method used easily in epidemiology cancer study.

描述（由申请人提供）： 摘要：随着癌症研究的不断深入，越来越多的癌症患者被治愈，并且不会复发或因癌症而死亡。鉴于患者的一系列风险因素，了解患者治愈的机会变得越来越重要，或者如果患者未治愈，了解某个时间的生存率也变得越来越重要。本计画的主要目的是发展一个新的、灵活的混合治愈模式，以估计治愈病人的比例，以及未治愈病人的存活机率。目前该领域的方法学假设治疗在试验的早期阶段是有效的，而新的模型可以允许治疗在初始时间没有效果，并且对于未治愈的患者，之后逐渐有效果。这种独特的功能，使所提出的模型是一个重要的替代模型，从业者或研究人员参与癌症流行病学研究建模删失生存数据与长期幸存者。我们将开发一个半参数估计方法，比较它与现有的模型和方法，评估所有模型的模拟研究，并将该模型应用于乳腺癌数据集。该研究将为临床医生分析癌症治愈率数据和评估风险效应提供重要工具。该软件在R环境下的开发将使混合治愈模型在癌症流行病学研究中的应用成为可能。 公共卫生关系： 随着癌症研究的进步，越来越多的癌症患者被治愈。本项目将研究一种新的模型，用于分析治愈患者的癌症生存数据。在R环境下的软件开发将使所提出的方法易于应用于癌症流行病学研究。