在风险评估中使用观察数据时,应用定量不确定性评估来确定合理的毒性值范围:一个审查全氟辛烷磺酸和全氟辛烷磺酸暴露与疫苗反应之间关系的案例研究。

IF 3.4 3区 医学 Q2 TOXICOLOGY
Daniele S Wikoff, Melissa J Vincent, Melissa M Heintz, Susan T Pastula, Heidi Reichert, William D Klaren, Laurie C Haws
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引用次数: 0

摘要

在确定毒性值时,需要对定量描述风险评估不确定性的传统方法进行调整,以适应对观察性(相对于实验性)研究的日益依赖。本文以全氟辛烷磺酸和全氟辛烷磺酸与疫苗反应为例,探讨了在使用观察数据时,对毒性价值发展过程中每一步的不确定性进行定性和可能的定量评估的方法,包括对个别研究的审查和评估、候选研究的选择、剂量-反应建模和不确定性因素的应用。确定的15项研究中的每一项都存在不确定性,这是由于在混淆、结果和暴露确定方面存在偏倚风险,可能导致研究内部和研究之间观察到的不一致,并导致缺乏剂量-反应评估的候选性。尽管如此,我们还是选择了两项具有代表性的研究来展示在剩余步骤中量化不确定性的可能方法。数据模拟表明缺乏明确的剂量-反应关系;符合代表性模拟的剂量-反应模型表明,效应的大小和方向都有很高的不确定性,模拟的BMDL值对全氟辛烷磺酸和全氟辛烷磺酸至少相差66倍和86倍。不确定因子的应用增加了最小的不确定度。综合起来,观察到高度的不确定性,排除了仅凭观测数据自信地评估因果剂量-反应关系的能力。本案例研究强调了在根据观察数据制定毒性值时需要进行定量不确定性分析,重要的是,强调了在依赖定量风险评估中的关联研究时,需要应用额外的技术来直接评估因果关系和剂量反应的特异性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of a quantitative uncertainty assessment to develop ranges of plausible toxicity values when using observational data in risk assessment: a case study examining associations between PFOA and PFOS exposures and vaccine response.

Traditional approaches for quantitatively characterizing uncertainty in risk assessment require adaptation to accommodate increased reliance on observational (vs experimental) studies in developing toxicity values. Herein, a case study with perfluorooctanoic acid (PFOA) and PFOS and vaccine response explores approaches for qualitative and-where possible-quantitative assessments of uncertainty at each step in the toxicity value development process when using observational data, including review and appraisal of individual studies, candidate study selection, dose-response modeling, and application of uncertainty factors. Each of the 15 studies identified had uncertainties due to risk of bias in confounding, outcome, and exposure ascertainment, likely contributing to the observed inconsistencies within and across studies, and resulting in lack of candidacy for dose-response assessment. Nonetheless, 2 representative studies were selected to demonstrate possible methods to quantify uncertainty in the remaining steps. Data simulations indicated lack of a clear dose-response relationship; dose-response models fit to representative simulations indicated high uncertainty in both the magnitude and direction of effect with simulated benchmark dose and its lower limit values varying at least 66- and 86-fold for PFOA and PFOS. Uncertainty factor application added minimal uncertainty. Combined, a high level of uncertainty was observed, precluding the ability to confidently assess causal dose-response relationships with the observational data, alone. This case study highlights the need for quantitative uncertainty analysis when developing toxicity values with observational data and, importantly, emphasizes the need for application of additional techniques to directly assess causality and the specificity of dose-response when relying on studies of association in quantitative risk assessment.

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来源期刊
Toxicological Sciences
Toxicological Sciences 医学-毒理学
CiteScore
7.70
自引率
7.90%
发文量
118
审稿时长
1.5 months
期刊介绍: The mission of Toxicological Sciences, the official journal of the Society of Toxicology, is to publish a broad spectrum of impactful research in the field of toxicology. The primary focus of Toxicological Sciences is on original research articles. The journal also provides expert insight via contemporary and systematic reviews, as well as forum articles and editorial content that addresses important topics in the field. The scope of Toxicological Sciences is focused on a broad spectrum of impactful toxicological research that will advance the multidisciplinary field of toxicology ranging from basic research to model development and application, and decision making. Submissions will include diverse technologies and approaches including, but not limited to: bioinformatics and computational biology, biochemistry, exposure science, histopathology, mass spectrometry, molecular biology, population-based sciences, tissue and cell-based systems, and whole-animal studies. Integrative approaches that combine realistic exposure scenarios with impactful analyses that move the field forward are encouraged.
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