Threshold Regression Methodology for Cancer Risk Assessment

描述(申请人提供)：在前期工作的基础上，我们建议开发一种新的流行病学研究统计方法，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。阈值回归基于这样一个看似合理的假设，即受试者的潜在健康状态是一个受疾病影响的随机过程，当受试者的潜在健康状态低于临界阈值时，最终会导致死亡或另一个不利终点。该方法在疾病进展量表中捕捉职业暴露的影响，该量表作为健康状况过程的修正时间量表。与现有的用于评估与职业暴露相关的疾病风险的分析方法相比，我们建议的方法的优点是：(A)它可以应用于定量和半定量的暴露数据；(B)与严重依赖比例危险假设的传统生存方法不同，建议的模型不依赖于这一假设；(C)它可以以自然的方式考虑多种相互竞争的健康风险；(D)它提供了从新的角度显示生存趋势的新型图表。本申请涉及NIOSH/NORA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。本项目旨在促进应用定量方法和统计研究，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，该模型可用于阐明个人和人群中与癌症风险相关的易感因素。具体目标是： 1.将阈值回归发展成为一种完善的职业风险评估实用工具。 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.