Systematic dose-response of environmental epidemiologic studies: Dose and response pre-analysis: Fid-Bau Portal

Systematic dose-response of environmental epidemiologic studies: Dose and response pre-analysis

Allen, Bruce / Shao, Kan / Hobbie, Kevin / Mendez, William Jr. / Lee, Janice S. / Cote, Ila / Druwe, Ingrid / Gift, Jeff / Davis, J. Allen

Abstract

Highlights • Often summary epidemiologic data needs pre-analysis before dose-response. • Estimated effective counts retain the control for confounders in individual studies. • Estimating dose metrics via probabilistic methods address interindividual variation. • The methods in this paper are suitable prior to individual study or meta-analyses.

Abstract Meta-analysis approaches can be used to assess the human risks due to exposure to environmental chemicals when there are numerous high-quality epidemiologic studies of priority outcomes in a database. However, methodological issues related to how different studies report effect measures and incorporate exposure into their analyses arise that complicate the pooled analysis of multiple studies. As such, there are “pre-analysis” steps that are often necessary to prepare summary data reported in epidemiologic studies for dose-response analysis. This paper uses epidemiologic studies of arsenic-induced health effects as a case example and addresses the issues surrounding the estimation of mean doses from censored dose- or exposure-intervals reported in the literature (e.g., estimation of mean doses from high exposures that are only reported as an open-ended interval), calculation of a common dose metric for use in a dose-response meta-analysis (one that takes into consideration inter-individual variability), and calculation of response “effective counts” that inherently account for confounders. The methods herein may be generalizable to 1) the analysis of other environmental contaminants with a suitable database of epidemiologic studies, and 2) any meta-analytic approach used to pool information across studies. A second companion paper detailing the use of “pre-analyzed” data in a hierarchical Bayesian dose-response model and techniques for extrapolating risks to target populations follows.