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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.
期刊论文(8)
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会议论文
DOI: 10.1016/j.cmpb.2013.10.001
发表时间: 2014
期刊: Computer methods and programs in biomedicine
影响因子: 6.1
作者: [Cai C, Wang S, Lu W, Zhang J]
通讯作者: Zhang J
DOI: 10.1016/j.csda.2012.09.017
发表时间: 2013-03
期刊: COMPUTATIONAL STATISTICS & DATA ANALYSIS
影响因子: 1.8
作者: [Zhang, Jiajia, Peng, Yingwei, Li, Haifen]
通讯作者: Li, Haifen
DOI: 10.1016/j.csda.2012.04.001
发表时间: 2012-12-01
期刊: COMPUTATIONAL STATISTICS & DATA ANALYSIS
影响因子: 1.8
作者: [Li, Haifen, Zhang, Jiajia, Tang, Yincai]
通讯作者: Tang, Yincai
DOI: 10.1007/s10985-009-9126-4
发表时间: 2009-12
期刊: Lifetime data analysis
影响因子: 1.3
作者: [Zhang J, Peng Y]
通讯作者: Peng Y
6
    Innovative Spatial Survival Models with Geographically Varying Coefficients
    Innovative Spatial Survival Models with Geographically Varying Coefficients
    Sample Size Method and Software Development in Survival Trial with a Cure Rate
    Sample Size Method and Software Development in Survival Trial with a Cure Rate
    国内基金
    海外基金
    层出镰刀菌氮代谢调控因子AreA 介导伏马菌素 FB1 生物合成的作用机理
    • 批准号:
      2021JJ40433
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2021
    • 负责人:
      孙磊
    • 依托单位:
    寄主诱导梢腐病菌AreA和CYP51基因沉默增强甘蔗抗病性机制解析
    • 批准号:
      32001603
    • 项目类别:
      青年科学基金项目
    • 资助金额:
      24.0万元
    • 批准年份:
      2020
    • 负责人:
      段真珍
    • 依托单位:
    AREA国际经济模型的移植.改进和应用
    • 批准号:
      18870435
    • 项目类别:
      面上项目
    • 资助金额:
      2.0万元
    • 批准年份:
      1988
    • 负责人:
      史树中
    • 依托单位: