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Updated: Sep 29, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Authors' rebuttal to Integrated Risk Information System (IRIS) response to "Assessing risk of bias in human
Stephanie M Eick1, Dana E Goin2, Juleen Lam2,3
1Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Abstract:
This letter responds to the US Environmental Protection Agency's Integrated Risk Information System (IRIS) program letter by Radke et al. (2021) that was published in response to the application of the IRIS risk of bias tool in our recent study "Assessing risk of bias in human environmental epidemiology studies using three tools: different conclusions from different tools." Their letter stated that we misrepresented the IRIS approach. Here, we respond to their three points raised and how we did not misrepresent their tool and also identified areas for improvement: (1) why it should be expected that different reviewers could reach different conclusions with the IRIS tool, as ratings are subject to reviewer judgment; (2) why our interpretation that "low" or "uninformative" studies could be excluded from a body of evidence was reasonable; and (3) why we believe the use of a rating system that generates an overall rating based on an individual domain or a combination of identified deficiencies essentially acts as a score and assumes that we know empirically how much each risk of bias domain should contribute to the overall rating for that study. We have elaborated on these points in our letter.
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