Threshold Regression Methodology for Cancer Risk Assessment

描述（由申请人提供）：在初步工作的基础上，我们建议为流行病学研究开发一种新的统计方法，称为阈值回归（TR），这将促进和丰富与职业暴露相关的健康风险评估。阈值回归基于合理假设，即受试者的潜在健康状态是受疾病影响的随机过程，当受试者的潜在健康状态福尔斯低于临界阈值时，最终导致死亡或其他不良终点。该方法捕捉职业暴露的影响，在疾病进展规模，作为一个修改的时间尺度的健康状况的过程。与现有的职业暴露相关疾病风险评估方法相比，我们提出的方法的优点是：（a）它可以应用于定量和半定量暴露数据;（B）与严重依赖比例危害假设的传统生存方法不同，我们提出的模型不依赖于这一假设;（c）它能以自然的方式考虑到多种相互竞争的健康风险;（d）它提供了新类型的图表，从新的角度显示生存趋势。本申请涉及NIOSH/诺拉优先研究领域的“研究工具和方法”类别中列出的风险评估方法。该项目旨在为应用定量方法和统计研究做出贡献，这些方法和研究可以模拟与工作相关的环境暴露和癌症风险之间的随机关系，该模型可用于阐明与个人和人群亚组中癌症风险相关的易感因素。具体目标是： 1.将阈值回归法发展成为职业风险评估的一个健全实用的工具。 2.量化危害和剂量-反应关系。 3.将该方法应用于两项大型职业研究。 4.开发必要的计算软件工具。

DESCRIPTION (provided by applicant): Building on preliminary work, we propose to develop a new statistical methodology for epidemiologic studies, called Threshold Regression (TR), that will facilitate and enrich the assessment of health risks associated with occupational exposures. Threshold regression is based on the plausible hypothesis that the latent health status of a subject is a random process that is affected by disease and ultimately results in death or another adverse endpoint when the subject's latent health status falls below a critical threshold value. The methodology captures effects of occupational exposure in a disease progression scale that acts as a modified time scale for the health status process. The advantages of our proposed methodology over existing analytic methods used to assess disease risk associated with occupational exposures are (a) it can be applied to both quantitative and semi-quantitative exposure data; (b) unlike traditional survival methods that depend heavily on the assumption of proportional hazards, the proposed model does not depend on this assumption; (c) it can take account of multiple competing health risks in a natural manner; (d) it provides new types of graphs that display survival trends from new perspectives. This application addresses Risk Assessment Methods listed in the "Research Tools and Approache's category of NIOSH/NORA Priority Research Areas. This project is aimed at contributing to applied quantitative methods and statistical research that can model the stochastic relationship between work-related environmental exposure and cancer risk, The model can be used for elucidation of susceptibility factors associated with cancer risk in individuals and population subgroups. Specific aims are: 1. Develop threshold regression into a sound practical tool for occupational risk assessment. 2. Quantify hazards and the dose-response relationship. 3. Apply the methodology to two large occupational studies. 4. Develop requisite computational software tools.