Statistical Methods for Multi-Chemical Toxicity Studies

多种化学品毒性研究的统计方法

• 批准号: 7968265
• 负责人: Gregg Dinse
• 金额: $ 16.76万
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7968265
• 关键词: Area; Bayesian Analysis; Binding; Chemicals; Classification; Data; Data Analyses; Development; Dioxins; Dose; Economics; Estrogens; Exhibits; Factor Analysis; Family; Goals; Least-Squares Analysis; Measures; Methods; Modeling; Nature; Non-linear Models; Operative Surgical Procedures; Pattern; Performance; Principal Component Analysis; Procedures; Relative (related person); Research; Research Personnel; Research Proposals; Simulate; Solutions; Statistical Methods; Techniques; Testing; Toxic effect; Weight; base; compound 17; direct application; interest; response

This is a new project, so at this point most of our efforts have been directed at developing a detailed research proposal. As outlined in this proposal, we expect to conduct research in five areas: (1) defining general relative potency functions in the context of nonlinear dose-response models, (2) developing statistical methods for making inferences about relative potency functions, (3) strengthening inferences by borrowing information across studies, (4) combining information from multiple endpoints, and (5) assessing performance by applying these techniques to real and simulated data. These five areas of research are described in more detail below. Area 1: Within a family of chemicals having the same mode of action, the relative potency of one chemical compared to another is the ratio of their doses producing the same toxic response. The standard definition of relative potency states that this ratio is constant for all dose (or response) levels. In the context of a nonlinear dose-response model, we will relax the usual assumption that relative potency is constant and instead allow for a variable measure. This generalization is important because conventional analyses often force a constancy assumption, even when the data suggest otherwise. Specifically, we will consider three options by expressing log relative potency as a function of log dose, response, and fractional increase in response above baseline. Area 2: We plan to develop procedures for making confidence statements and testing hypotheses about the relative potency function. We will assume a nonlinear model for the dose-response function and use generalized least squares methods to estimate the model parameters (and their standard errors), which in turn will be used to estimate the log relative potency function. For a given pair of chemicals, we intend to construct pointwise confidence intervals at specific doses or responses, as well as confidence bounds for the entire log relative potency function. Also, we plan to test hypotheses about the log relative potency function being flat, and in particular zero, over certain regions. For three or more chemicals, we intend to test whether the log relative potency functions cross and whether one function dominates another over certain regions. Area 3: When dose-response data are available from multiple studies, we will extend our methods to strengthen inferences by borrowing information across studies. Specifically, if several studies of the same chemicals are performed and all involve a common endpoint, we will use techniques for hierarchical nonlinear models to incorporate random effects centered on a set of mean parameters. We will construct a log relative potency function from the mean dose-response parameters and extend our methods to make inferences about chemical-specific potencies based on the constructed log relative potency function. Area 4: Assuming a chemical exhibits toxicity through changes in several measures of response, we will investigate methods for the simultaneous analysis of multiple endpoints to assess the overall negative impact of the chemical. Many researchers are interested in how to best combine information from multiple endpoints, but presently there is no satisfactory solution. Direct application of the techniques developed for combining information over studies will not generally be applicable because different endpoints may have very different dose-response functions; thus, estimating an "average" curve will not always be appropriate. We will explore methods for defining groups of endpoints having similar dose-response patterns, for combining information within groups, and for summarizing results across groups (and assessing relative potencies across chemicals). We plan to collaborate with toxicologists to categorize endpoints and to develop a hierarchical model that nests endpoints within groups. We will also consider data-driven methods that borrow ideas from factor analysis and principal component analysis, as well as the use of expert classifications to help form prior distributions in a Bayesian analysis. Area 5: The NTP recently studied several responses to dioxin-like compounds and estimated a constant relative potency for each combination of chemical and toxicity endpoint. We plan to apply our methods to these data to estimate non-constant relative potency functions, to make confidence statements, and to test hypotheses. We intend to perform endpoint-specific analyses, as well as an analysis that combines information across endpoints. We also have dose-response data on 6 estrogenic compounds from 17 studies performed for the Organisation for Economic Co-operation and Development, all of which focused on uterine weight as the endpoint. We plan to analyze these data with the methods developed for borrowing information across studies. In addition to these analyses of real data, we will simulate data from a variety of situations, which will allow us evaluate the proposed methods in the context of knowing the true state of nature.

这是一个新项目，因此在这一点上，我们大多数努力都致力于制定详细的研究建议。 如本提案中概述的那样，我们希望在五个领域进行研究：（1）在非线性剂量响应模型的背景下定义一般相对效能函数，（2）开发统计方法来推断相对效能函数的推断，（3）通过在多个端点和5）进行仿真的信息中借用信息来加强推断的推理，并通过应用这些技术进行计算和数据，并将这些技术组合到这些技术和数据中。 下面更详细地介绍了这五个研究领域。 区域1： 在具有相同作用方式的化学物质家族中，与另一种化学物质相比，一种化学物质的相对效力是它们产生相同有毒反应的剂量之比。 相对效力的标准定义指出，对于所有剂量（或响应）水平，该比率是恒定的。 在非线性剂量反应模型的背景下，我们将放宽通常的假设，即相对效力是恒定的，而是允许可变度量。 这种概括很重要，因为传统分析通常会迫使一个恒定假设，即使数据暗示了另有建议。 特别是，我们将通过表达对数相对效力的函数来考虑三个选项，这是对数剂量，响应和基线响应的分数增加的函数。 区域2： 我们计划制定制作信心陈述并测试相对效能函数的假设的程序。 我们将假设剂量反应函数的非线性模型，并使用通用的最小二乘方法估计模型参数（及其标准误差），而该参数又将用于估计对数相对效力函数。 对于给定的一对化学物质，我们打算以特定剂量或反应的特定剂量构造置态间隔，以及整个对数相对效力函数的置信界。 此外，我们计划测试有关对数相对效力函数平坦的假设，尤其是在某些区域中为零。 对于三种或多个化学物质，我们打算测试对数相对效力的功能是否交叉以及一个功能是否在某些区域中占主导地位。 区域3： 当从多个研究中获得剂量反应数据时，我们将扩展我们的方法以通过跨研究借贷信息来增强推论。 具体而言，如果对相同化学物质进行了几项研究，并且所有研究都涉及一个共同的终点，则我们将使用层次非线性模型的技术来纳入以一组平均参数为中心的随机效应。 我们将从平均剂量反应参数中构建对数相对效能函数，并扩展我们的方法，以根据构造的对数相对效力函数来推断化学特异性效力。 区域4： 假设化学物质通过几种响应度量的变化表现出毒性，我们将研究对多个终点的同时分析的方法，以评估化学物质的总体负面影响。 许多研究人员对如何最好地结合来自多个终点的信息感兴趣，但是目前没有令人满意的解决方案。 直接应用用于将信息结合到研究中的技术通常不适用，因为不同的端点可能具有截然不同的剂量反应函数。因此，估计“平均”曲线并不总是合适的。 我们将探讨定义具有相似剂量反应模式的端点组的方法，以组合组内的信息以及跨组的结果（以及评估化学品跨化学品的相对效力）。 我们计划与毒理学家合作，分类端点，并开发一个在组中筑巢的层次模型。 我们还将考虑以数据驱动的方式从因子分析和主要成分分析中借用思想的方法，以及使用专家分类来帮助在贝叶斯分析中形成先前的分布。 区域5： NTP最近研究了对二恶英类化合物的几种反应，并估计化学和毒性终点的每种组合都有恒定的相对效力。 我们计划将我们的方法应用于这些数据，以估计非恒定相对效力函数，制作置信度声明并检验假设。 我们打算执行特定于端点的分析，以及将信息跨端点组合结合的分析。 我们还提供了针对经济合作与发展组织进行的17种研究的6种雌激素化合物的剂量反应数据，所有这些研究都集中在子宫体重作为终点上。 我们计划使用用于跨研究的借贷信息开发的方法来分析这些数据。 除了对真实数据的分析外，我们还将模拟来自各种情况的数据，这将使我们在了解自然状态的背景下评估所提出的方法。