Lognormal Model for Determining Dose-Response Curves from Epidemiological Data and for Health Risk Assessment

2001 ◽  
Vol 16 (7) ◽  
pp. 745-754 ◽  
Author(s):  
Bernard E. Saltzman
Author(s):  
Philip E Goodrum ◽  
Janet K Anderson ◽  
Anthony L Luz ◽  
Graham K Ansell

Abstract Environmental occurrence and biomonitoring data for per- and polyfluoroalkyl substances (PFAS) demonstrate that humans are exposed to mixtures of PFAS. This article presents a new and systematic analysis of available PFAS toxicity study data using a tiered mixtures risk assessment framework consistent with United States and international mixtures guidance. The lines of evidence presented herein include a critique of whole mixture toxicity studies and analysis of dose-response models based on data from subchronic oral toxicity studies in rats. Based on available data to-date, concentration addition and relative potency factor methods are found to be inappropriate due to differences among sensitive effects and target organ potencies and noncongruent dose-response curves for the same effect endpoints from studies using the same species and protocols. Perfluorooctanoic acid and perfluorooctane sulfonic acid lack a single mode of action or molecular initiating event and our evaluation herein shows they also have noncongruent dose-response curves. Dose-response curves for long-chain perfluoroalkyl sulfonic acids (PFSAs) also significantly differ in shapes of the curves from short-chain PFSAs and perfluoroalkyl carboxylic acids evaluated, and additional differences are apparent when curves are evaluated based on internal or administered dose. Following well-established guidance, the hazard index method applied to perfluoroalkyl carboxylic acids and PFSAs grouped separately is the most appropriate approach for conducting a screening level risk assessment for nonpolymeric PFAS mixtures, given the current state-of-the science. A clear presentation of assumptions, uncertainties, and data gaps is needed before dose-additivity methods, including hazard index , are used to support risk management decisions. Adverse outcome pathway(s) and mode(s) of action information for perfluorooctanoic acid and perfluorooctane sulfonic acid and for other nonpolymer PFAS are key data gaps precluding more robust mixtures methods. These findings can guide the prioritization of future studies on single chemical and whole mixture toxicity studies.


2002 ◽  
Vol 21 (7) ◽  
pp. 391-393
Author(s):  
M O Brophy

Quantitative health risk assessment is based on extrapolating from the high-dose end of the dose–response curve to points close to the origin or the threshold where the dose levels are closer to the lower environmental or occupational exposures. Hormesis is demonstrated in chronic toxicological studies where the animals treated at the lowest experimental dose appear to be healthier than the controls, as evidenced by longer life spans, less disease and/or increased body weight. If the occupational exposure limit (OEL) or environmental exposure limit (EEL) is in the range of the hormetic effect, or lower than the hormetic effect, then a case could be made that exposure at the OEL or EEL is `safe.’ This idea is controversial because it challenges some of the basic assumptions of quantitative health risk assessment as it has been practiced during the past 50 years. De-emphasis of the dose–response curve in determining OELs and EELs will occur not because of hormesis, but because the emerging sciences of genomics and proteomics will shift the focus from statistical methods to individuals as genetic and protein engineering becomes more sophisticated and powerful.


2005 ◽  
Vol 24 (5) ◽  
pp. 249-253 ◽  
Author(s):  
Kirk T Kitchin ◽  
J Wanzer Drane

There are severe problems and limitations with the use of hormesis as the principal dose-response default assumption in risk assessment. These problems and limitations include: (a) unknown prevalence of hormetic doseresponse curves; (b) random chance occurrence of hormesis and the shortage of data on the repeatability of hormesis; (c) unknown degree of generalizability of hormesis; (d) there are dose-response curves that are not hormetic, therefore hormesis cannot be universally generalized; (e) problems of post hoc rather than a priori hypothesis testing; (f) a possible large problem of ‘false positive’ hormetic data sets which have not been extensively replicated; (g) the ‘mechanism of hormesis’ is not understood at a rigorous scientific level; (h) in some cases hormesis may merely be the overall sum of many different mechanisms and many different dose-response curves - some beneficial and some toxic. For all of these reasons, hormesis should not now be used as the principal dose-response default assumption in risk assessment. At this point, it appears that hormesis is a long way away from common scientific acceptance and wide utility in biomedicine and use as the principal default assumption in a risk assessment process charged with ensuring public health protection.


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