Abstract
Prompt cellular proliferation, resulting from toxic hyperplasia and/or normal tissue homeostasis, is required to complete carcinogenic initiation processes. Also, cell proliferation is required for carcinogenic potentiation. We have developed a mathematical model for tumorigenesis incorporating four dimensions: (1) dose, (2) exposure time, (3) sacrifice time, and (4) response. The model is based on the mechanism of compensatory cell proliferation. The fit was tested against data for tumors observed in 24, 192 BALB/C mice fed 2-AAF at concentrations of 0, 35, 45, 60, 75, 100, and 150 ppm to time-of-sacrifice at 9, 12, 14, 15, 16, 17, 18, 24, and 33 months at the National Center for Toxicological Research (NCTR). Because this study was designed to measure a dose of 2-AAF needed to induce a 1% tumor rate, it has become commonly known as the ED01 study. The coefficients of the mathematical model were determined from the ED01 data and the model was then used to predict the time- and dose-development of tumors in a second NCTR study of mice fed 2-AAF at concentrations of 60, 75, 100, and 150 ppm for 9, 12, and 15 months, and then sacrificed at 18 and 24 months. Previous dose-response models have not described the ED01 study adequately. In contrast, this four-dimensional analysis fits the dose-response quite adequately (when timeon-feed is the same as time-to-sacrifice) and is also totally predictive (without any redetermination of numerical coefficients) for the feed-waitsacrifice protocol.
Research sponsored by the Office of Health and Environmental Research, U.S. Department of Energy, under contract DE-AC05-84 OR21400 with Martin Marietta Energy Systems, Inc.
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© 1987 Plenum Press, New York
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Jones, T.D., Dudney, C.S., Walsh, P.J. (1987). Multiple Time Measures are Necessary to Reduce Uncertainty in Dose-Response Modeling: Time- and Dose-Mechanisms of the ED01 Study. In: Covello, V.T., Lave, L.B., Moghissi, A., Uppuluri, V.R.R. (eds) Uncertainty in Risk Assessment, Risk Management, and Decision Making. Advances in Risk Analysis, vol 4. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5317-1_29
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DOI: https://doi.org/10.1007/978-1-4684-5317-1_29
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