Fedak Kristen M, Bernal Autumn, Capshaw Zachary A, Gross Sherilyn
Department of Environmental and Radiological Health Sciences, Colorado State University, 350 West Lake Street, Fort Collins, CO 80521 USA ; Cardno ChemRisk, 4840 Pearl East Circle, Suite 300 West, Boulder, CO 80301 USA.
Cardno ChemRisk, 130 Vantis Suite 170, Aliso Viejo, CA 92656 USA.
Emerg Themes Epidemiol. 2015 Sep 30;12:14. doi: 10.1186/s12982-015-0037-4. eCollection 2015.
In 1965, Sir Austin Bradford Hill published nine "viewpoints" to help determine if observed epidemiologic associations are causal. Since then, the "Bradford Hill Criteria" have become the most frequently cited framework for causal inference in epidemiologic studies. However, when Hill published his causal guidelines-just 12 years after the double-helix model for DNA was first suggested and 25 years before the Human Genome Project began-disease causation was understood on a more elementary level than it is today. Advancements in genetics, molecular biology, toxicology, exposure science, and statistics have increased our analytical capabilities for exploring potential cause-and-effect relationships, and have resulted in a greater understanding of the complexity behind human disease onset and progression. These additional tools for causal inference necessitate a re-evaluation of how each Bradford Hill criterion should be interpreted when considering a variety of data types beyond classic epidemiology studies. Herein, we explore the implications of data integration on the interpretation and application of the criteria. Using examples of recently discovered exposure-response associations in human disease, we discuss novel ways by which researchers can apply and interpret the Bradford Hill criteria when considering data gathered using modern molecular techniques, such as epigenetics, biomarkers, mechanistic toxicology, and genotoxicology.
1965年,奥斯汀·布拉德福德·希尔爵士发表了九条“观点”,以帮助确定观察到的流行病学关联是否具有因果关系。从那时起,“布拉德福德·希尔标准”已成为流行病学研究中因果推断最常被引用的框架。然而,当希尔发表他的因果指南时——距离DNA双螺旋模型首次提出仅12年,距离人类基因组计划开始还有25年——当时对疾病因果关系的理解比现在更为基础。遗传学、分子生物学、毒理学、暴露科学和统计学的进步提高了我们探索潜在因果关系的分析能力,并使我们对人类疾病发生和发展背后的复杂性有了更深入的理解。这些用于因果推断的额外工具需要重新评估在考虑经典流行病学研究之外的各种数据类型时,应如何解释每条布拉德福德·希尔标准。在此,我们探讨数据整合对这些标准的解释和应用的影响。通过人类疾病中最近发现的暴露-反应关联的例子,我们讨论研究人员在考虑使用现代分子技术(如表观遗传学、生物标志物、机制毒理学和遗传毒理学)收集的数据时,应用和解释布拉德福德·希尔标准的新方法。