Translational mixed-factor benchmark-dose risk assessment

项目总结/摘要 量化有害输入的有害风险是疾病风险评估的一个关键组成部分。虽然 风险分析中的统计方法已经针对单一危险暴露进行了充分的研究，但仍存在关键差距 在这些方法的实际开发中，当混合输入因素可能影响不良结果时， 正在研究中。这个小型的，独立的研究项目的重点是开发和研究新的方法， 用于定量风险评估的统计推断，重点是混合定量和定性 输入因素。项目的重点将集中在与预辐射相关的基准剂量（BMD）的估计上。 选择的基准响应水平（BMR）。受翻译风险分析应用程序的启发， 儿童呼吸道疾病，该研究项目将开发用于开发基准标志物的方法 (the当额外的、定性的、多水平的因素对健康状况的影响至关重要时， 分析.将建立估计量的理论渐近特性，并从这些大的- 将构建样本基准剂量置信限（BMDLs）。 除了针对儿童呼吸系统健康的应用外，预期转化应用于 任何生物医学、毒理学、药理学、环境或职业研究， 数据被用来设定基准标志物或其他安全、低剂量水平，并有混合投入。所得 在处理联合暴露时，指南将改善公共卫生规划和疾病风险管理 有害物剂/混合投入物的组合可能相互作用或以其他方式共同作用， 疾病 该研究将填补多因素基准分析的关键空白，并将具有潜在的转化价值。 应用于各种公共卫生场景中的非标准/非传统环境。评价 该项目的各个阶段将通过蒙特卡罗方法研究估计量的小样本操作特性 计算机计算，并将探讨该方法的实际应用能力与激励 儿童哮喘的数据。目的是评估该方法的（1）实际能力，以及（2） 在这些平移设置中估计基准剂量的可行性。经验证的BMD程序 估计和计算置信限将被编码供公众使用，并移植到下载网站（S） 在互联网上，以促进分散在尽可能广泛的用户群体。

Project Summary/Abstract Quantifying detrimental risks from hazardous inputs is a critical component in disease risk evaluation. Although statistical methods in risk analysis have been well-studied for a single hazardous exposure, a critical gap exists in the practical development of these methods when mixed input factors might affect the adverse outcome(s) under study. The focus of this small, self-contained research project is to develop and study new methods of statistical inference for use in quantitative risk assessment, with focus on mixed quantitative and qualitative input factors. Project emphasis will center on estimation of benchmark doses (BMDs) associated with a pre- selected level of benchmarked response (BMR). Motivated by a translational risk-analytic application in childhood respiratory disease, this research project will develop methods for developing benchmark markers (the “doses”) of an adverse health outcome when additional, qualitative, multi-level factors are critical to the analysis. The theoretical, asymptotic characteristics of the estimators will be established, and from these large- sample benchmark dose confidence limits (BMDLs) will be constructed. Besides the targeted application to childhood respiratory health, translational application is anticipated for any biomedical, toxicological, pharmacological, environmental, or occupational studies where human or animal data are used to set benchmark markers or other safe, low-dose levels with mixed inputs. The resulting guidelines will improve public health planning and disease risk management when dealing with joint exposures where combinations of harmful agents/mixed inputs may interact or otherwise act jointly to amplify risk of disease. The research will fill critical gaps in multi-factor benchmark analysis, and will have potential translational application to non-standard/non-traditional settings across a wide variety of public health scenarios. Evaluation phases of the project will study the small-sample operating characteristics of the estimators via Monte Carlo computer calculations, and will explore the methodology's capabilities for practical application with motivating data on childhood asthma. The aim will be to assess the methodology's (1) practical capabilities, and (2) its viability for estimating benchmark doses in these translational settings. The validated procedures for BMD estimation and for calculating the confidence limits will be coded for public use and ported to download site(s) on the Internet to facilitate dispersal across the widest possible corps of users.