A new commentary published in November 2014 issue of the peer-reviewed journal Environmental Health Perspectives (EHP) offers a set of recommendations and guidelines aiming to help researchers to characterize uncertainty in epidemiological findings more effectively. The commentary is an outcome of a workshop organized by the Health and Environmental Sciences Institute (HESI) in Research Triangle Park, North Carolina, U.S., on October 22-23, 2012. At the meeting, experts from academia, government, and industry discussed the use of epidemiologic data in risk assessments, including the application of analytic methods to address sources of uncertainty. Uncertainty is associated with the results of most epidemiologic studies. The recommendations in the commentary encourage the use of specific statistical approaches and analytic techniques e.g. quantitative bias analysis, Directed-Acyclic Graphs (DAGs), and Bayesian analyses, to improve the inferences drawn from epidemiologic results. The authors highlight the need for new exposure assessment and uncertainty characterization methods to account for chemical mixtures. Finally, they stress that scientific journals commonly accept manuscripts that are lacking uncertainty analysis, validated exposure assessment, or use of advanced analytic methods. They suggest that funding organizations, peer reviewers, and journal editors should act as catalysts for stimulating change.
Carrie Arnold (November, 2014). “Thinking one step ahead: strategies to strengthen epidemiological data for use in risk assessment.” Environmental Health Perspectives (News), 122, A311.
Burns, C. et al., 2014. “Evaluating uncertainty to strengthen epidemiologic data for use in human health risk assessments.” Environmental Health Perspectives, 122, 1160–1165.