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Updated: Mar 26, 2026

High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC
Published on: May 10, 2016
The bottom-up approach to bounding potential low-dose cancer risks from formaldehyde: An update
Thomas B Starr1, James A Swenberg2
1TBS Associates, 7500 Rainwater Road, Raleigh, NC 27615, USA; Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, 166 Rosenau Hall, CB #7431, Chapel Hill, NC 27599-7431, USA.
Abstract:
In 2013, we proposed a novel bottom-up approach to bounding low-dose cancer risks that may result from small exogenous exposures to chemicals that are always present in the body as a result of normal biological processes. The approach utilizes the background cancer risk and the background (endogenous) concentration of a cancer-related exposure biomarker in specific target tissues. After allowing for statistical uncertainty in these two parameters, the ratio of the background risk to background exposure provides a conservative slope factor estimate that can be utilized to bound the added risk that may be associated with incremental exogenous exposures. Our original bottom-up estimates were markedly smaller than those obtained previously by the US Environmental Protection Agency (USEPA) with a conventional top-down approach to modeling nasopharyngeal cancer and leukemia mortality data from a US worker cohort. Herein we provide updated bottom-up estimates of risk for these two cancers that are smaller still, and rely upon more robust estimates of endogenous and exogenous formaldehyde-DNA adducts in monkeys and a more robust estimate of the DNA adduct elimination half-life in rats, both obtained very recently. We also re-examine the worker mortality data used by USEPA in developing its estimate of human leukemia incidence from lifetime exposure to 1 ppm airborne formaldehyde. Finally, we compare a new bottom-up slope estimate of the risk of rat nasal cancer with conventional top-down estimates obtained with empirical dose-response modeling of rat nasal cancer bioassay data.
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