Time-Variant Effects of Cancer Risk Factors in Nested Case-Control Studies

巢式病例对照研究中癌症危险因素的时变效应

基本信息

  • 批准号:
    8100321
  • 负责人:
  • 金额:
    $ 8.43万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-08-01 至 2013-07-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): In many cancer epidemiology cohort studies, the disease of interest is often rare but the study hypothesis is complex with a large number of risk factors. These studies usually require a long-term follow-up to obtain an adequate number of cancer events and to elucidate the course of the disease. Therefore, it can be prohibitively expensive to assemble data for the entire cohort. Nested case-control (NCC) design is a popular sampling method prominently due to its cost-effectiveness. In practice, NCC data are commonly analyzed using Cox's proportional hazards (PH) model. A direct consequence of the PH model is that the ratio of hazard functions with different covariate values is assumed to remain constant over the entire follow-up period. Due to the nature of long-term observation and complexity of the relationship to be explored in large-scale cancer studies, the proportional hazards assumption may easily be violated. Therefore, extensions of Cox's model to accommodate time-varying covariate effects not only are necessary to improve the modeling 0exibility but also are critical to elucidate the etiology of cancer. However, methodology developments for such 0exible models have been mainly focused on cohort studies and their uses in NCC studies remain limited. In this project, we propose to study the Cox model with time-varying coe1cients to characterize temporal effects of cancer risk factors in NCC studies. In Aim 1, we propose to develop statistical methodologies to estimate the time-varying coe1cient functions using a kernel-weighted partial likelihood approach; to construct point-wise and simultaneous confidence intervals of the estimated time-varying coe1cients; to test and identify the existence of time-varying effect of specific risk factor; and to investigate the variable selection problem in the Cox model with time-varying coe1cients for NCC data. Once the asymptotic properties of the proposed method are established in theory and the inference procedures are validated using extensive Monte Carlo simulation studies, we can implement our proposed approaches to pursue Aim 2, which will focus on real data analyses and software development. The first part of Aim 2 will be accomplished through collaborations with the New York University Women Health Study (NYUWHS). Then developing and contributing an open-source R package will make the proposed methodologies freely available to practical researchers. Successful completion of the proposed studies will provide a series of advanced statistical inference approaches to elucidating the temporal effects of risk factors on the cancer development for NCC studies, which will also substantially improve our modeling 0exibility in the analysis of NCC data, and can assess and validate the results obtained from other methods. Furthermore, the application in NYUWHS will provide us new insights and better understanding on the effects of potential risk factors in cancer etiology. The fund mental contribution of development of freely-available software package is that it will translate the advanced statistical methodologies into practically useful and accessible tools. PUBLIC HEALTH RELEVANCE: PROJECT NARRATIVE: Nested case-control design, a cost-effective sampling method commonly used in cancer epidemiologic studies, necessitates developing 0exible statistical approaches to evaluate the association between cancer and risk factors. This research project proposes to develop statistical models and inference approaches to accommodating and characterizing temporal effects of cancer risk factors for NCC studies, to provide new aspects and novel insights into the temporal relation between disease and its risk factors, and to elucidate our understanding of cancer etiology. Furthermore, contributing freely available software is essential to equip practical investigators with alternative tools to analyze NCC data and to assess, compare and validate study results.
描述(由申请人提供):在许多癌症流行病学队列研究中,感兴趣的疾病通常很少见,但研究假设很复杂,有大量危险因素。这些研究通常需要长期随访才能获得足够数量的癌症事件并阐明疾病的进程。因此,在整个队列中组装数据可能非常昂贵。嵌套的情况对照(NCC)设计是一种流行的抽样方法,由于其成本效益。实际上,通常使用COX的比例危害(PH)模型对NCC数据进行分析。 pH模型的直接结果是,假定具有不同协变量值的危险函数在整个随访期间保持恒定。由于在大规模癌症研究中要探讨的长期观察和复杂性的性质,因此很容易违反比例危害假设。因此,Cox模型的扩展以适应时间变化的协变量效应,不仅需要提高建模0算法,而且对于阐明癌症的病因至关重要。然而,这种0符合模型的方法发展主要集中在队列研究上,而在NCC研究中的使用仍然有限。在这个项目中,我们建议使用随时间变化的COE1CINTS研究COX模型,以表征NCC研究中癌症风险因素的时间影响。在AIM 1中,我们建议开发统计方法,以使用内核加权的部分可能性方法来估计随时间变化的COE1CIENT函数;构建估计的时变COE1cients的点和同时置信区间;测试和确定特定危险因素的时变作用的存在;并研究COX模型中的可变选择问题,其中包括随时间变化的COE1cients用于NCC数据。一旦在理论上建立了所提出的方法的渐近性能,并使用大量的蒙特卡洛模拟研究对推理程序进行验证,我们就可以实施我们提出的方法来追求AIM 2,该方法将重点关注实际数据分析和软件开发。 AIM 2的第一部分将通过与纽约大学妇女健康研究(NYUWHS)的合作来完成。然后开发并贡献开源R包将使建议的方法可以免费提供给实践研究人员。成功完成拟议的研究将提供一系列先进的统计推断方法,以阐明危险因素对NCC研究的癌症发展的时间影响,这也将大大提高我们在NCC数据分析中的建模0的允许,并可以评估和验证从其他方法中获得的结果。此外,NYUWH的应用将为我们提供新的见解,并更好地了解潜在危险因素对癌症病因的影响。自由开发软件包开发的基金心理贡献是,它将将先进的统计方法转化为实际有用且可访问的工具。 公共卫生相关性:项目叙述:嵌套的病例对照设计,一种经济高效的抽样方法,通常用于癌症流行病学研究,需要开发0个可裁定的统计方法来评估癌症与危险因素之间的关联。该研究项目建议开发统计模型和推理方法,以适应和表征NCC研究的癌症风险因素的时间影响,以提供有关疾病及其危险因素之间时间关系的新方面和新的见解,并阐明我们对癌症病因的理解。此外,免费提供的软件对于为实用研究人员提供了分析NCC数据并评估,比较和验证研究结果的替代工具至关重要。

项目成果

期刊论文数量(0)
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Mengling Liu其他文献

Mengling Liu的其他文献

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{{ truncateString('Mengling Liu', 18)}}的其他基金

Complex WTC Exposures Impacting Persistent Large and Small Airflow Limitation and Vulnerable Subgroups in the WTC Survivor Population
复杂的世贸中心暴露影响了世贸中心幸存者群体中持续的大、小气流限制和弱势群体
  • 批准号:
    10749125
  • 财政年份:
    2023
  • 资助金额:
    $ 8.43万
  • 项目类别:
SEMIPARAMETRIC METHODS FOR MODELING OF TIME-DEPENDENT ENVIRONMENTAL EXPOSURES
时变环境暴露建模的半参数方法
  • 批准号:
    10180693
  • 财政年份:
    2021
  • 资助金额:
    $ 8.43万
  • 项目类别:
SEMIPARAMETRIC METHODS FOR MODELING OF TIME-DEPENDENT ENVIRONMENTAL EXPOSURES
时变环境暴露建模的半参数方法
  • 批准号:
    10388399
  • 财政年份:
    2021
  • 资助金额:
    $ 8.43万
  • 项目类别:
SEMIPARAMETRIC METHODS FOR MODELING OF TIME-DEPENDENT ENVIRONMENTAL EXPOSURES
时变环境暴露建模的半参数方法
  • 批准号:
    10552047
  • 财政年份:
    2021
  • 资助金额:
    $ 8.43万
  • 项目类别:
Integration and Evaluation of Pooled Cancer Studies with Heterogeneity
具有异质性的汇总癌症研究的整合和评估
  • 批准号:
    8628809
  • 财政年份:
    2013
  • 资助金额:
    $ 8.43万
  • 项目类别:
Integration and Evaluation of Pooled Cancer Studies with Heterogeneity
具有异质性的汇总癌症研究的整合和评估
  • 批准号:
    8509297
  • 财政年份:
    2013
  • 资助金额:
    $ 8.43万
  • 项目类别:
Biomarkers and Breast Cancer Risk Prediction in Younger Women
年轻女性的生物标志物和乳腺癌风险预测
  • 批准号:
    8561500
  • 财政年份:
    2013
  • 资助金额:
    $ 8.43万
  • 项目类别:
Biomarkers and Breast Cancer Risk Prediction in Younger Women
年轻女性的生物标志物和乳腺癌风险预测
  • 批准号:
    8731842
  • 财政年份:
    2013
  • 资助金额:
    $ 8.43万
  • 项目类别:
Time-Variant Effects of Cancer Risk Factors in Nested Case-Control Studies
巢式病例对照研究中癌症危险因素的时变效应
  • 批准号:
    7991942
  • 财政年份:
    2010
  • 资助金额:
    $ 8.43万
  • 项目类别:

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