Applying the Bradford Hill criteria in the 21st century: How data integration has changed causal inference in molecular epidemiology

被引:433
作者
Fedak K.M. [1 ,3 ]
Bernal A. [2 ]
Capshaw Z.A. [3 ]
Gross S. [3 ]
机构
[1] Department of Environmental and Radiological Health Sciences, Colorado State University, 350 West Lake Street, Fort Collins, 80521, CO
[2] Cardno ChemRisk, 130 Vantis Suite 170, Aliso Viejo, 92656, CA
[3] Cardno ChemRisk, 4840 Pearl East Circle, West, Boulder, 80301, CO
来源
Emerging Themes in Epidemiology | / 12卷 / 1期
关键词
Bradford Hill; Causal inference; Causation; Data integration; Molecular epidemiology;
D O I
10.1186/s12982-015-0037-4
中图分类号
学科分类号
摘要
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. © 2015 Fedak et al.
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