Translational mixed-factor benchmark-dose risk assessment

项目摘要/摘要 量化危险投入物的有害风险是疾病风险评估中的一个关键组成部分。虽然 风险分析中的统计方法对于单一的危险暴露已经进行了很好的研究，存在着严重的差距 在这些方法的实际开发中，当混合输入因素可能影响不利结果时(S) 正在研究中。这个小型而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 投入因素。项目重点将集中在与Pre-Rate相关的基准剂量估计(BMD)上 选定的基准响应级别(BMR)。受以下方面的翻译风险分析应用程序的推动 儿童呼吸道疾病，这项研究项目将开发基准标记物的方法 (“剂量”)当额外的、定性的、多层次的因素对 分析。将建立估计量的理论上的渐近特征，并从这些大的- 将建立样本基准剂量置信限(BMDL)。 除了针对儿童呼吸健康的目标应用外，预计还将针对 任何生物医学、毒理学、药理学、环境或职业研究，而人类或动物 数据被用来设置基准标记或其他混合输入的安全、低剂量水平。由此产生的 指导方针将在处理联合暴露时改进公共卫生规划和疾病风险管理 有害物质/混合投入物的组合可能相互作用或以其他方式共同作用以放大 疾病。 这项研究将填补多因素基准分析中的关键空白，并将具有潜在的翻译价值 适用于各种公共卫生情景中的非标准/非传统环境。评估 该项目的各个阶段将通过蒙特卡洛方法研究估计器的小样本运行特性 计算机计算，并将探索该方法在实际应用中的能力 关于儿童哮喘的数据。其目的将是评估该方法的(1)实践能力和(2)其 在这些翻译环境中估计基准剂量的可行性。有效的骨密度检查程序 估计和计算置信限将编码供公众使用，并移植到下载网站(S) 以便于在尽可能广泛的用户群体中传播。

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.