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Application of probabilistic methods to address variability and uncertainty in estimating risks for non-cancer health effects.

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Title: Application of probabilistic methods to address variability and uncertainty in estimating risks for non-cancer health effects.
Authors: Nielsen, Greylin H.1 (AUTHOR), Heiger-Bernays, Wendy J.1 (AUTHOR) whb@bu.edu, Levy, Jonathan I.1 (AUTHOR), White, Roberta F.1 (AUTHOR), Axelrad, Daniel A.2 (AUTHOR), Lam, Juleen3 (AUTHOR), Chartres, Nicholas4 (AUTHOR), Abrahamsson, Dimitri Panagopoulos4 (AUTHOR), Rayasam, Swati D. G.4 (AUTHOR), Shaffer, Rachel M.5 (AUTHOR), Zeise, Lauren6 (AUTHOR), Woodruff, Tracey J.4 (AUTHOR), Ginsberg, Gary L.7 (AUTHOR)
Source: Environmental Health: A Global Access Science Source. 1/12/2023, Vol. 21 Issue 1, p1-13. 13p.
Subject Terms: *Health risk assessment, *Poisons, Estimates, Cost effectiveness, Central nervous system, Risk assessment, Probabilistic number theory, Disease risk factors
Company/Entity: United States. Environmental Protection Agency
Abstract: Human health risk assessment currently uses the reference dose or reference concentration (RfD, RfC) approach to describe the level of exposure to chemical hazards without appreciable risk for non-cancer health effects in people. However, this "bright line" approach assumes that there is minimal risk below the RfD/RfC with some undefined level of increased risk at exposures above the RfD/RfC and has limited utility for decision-making. Rather than this dichotomous approach, non-cancer risk assessment can benefit from incorporating probabilistic methods to estimate the amount of risk across a wide range of exposures and define a risk-specific dose. We identify and review existing approaches for conducting probabilistic non-cancer risk assessments. Using perchloroethylene (PCE), a priority chemical for the U.S. Environmental Protection Agency under the Toxic Substances Control Act, we calculate risk-specific doses for the effects on cognitive deficits using probabilistic risk assessment approaches. Our probabilistic risk assessment shows that chronic exposure to 0.004 ppm PCE is associated with approximately 1-in-1,000 risk for a 5% reduced performance on the Wechsler Memory Scale Visual Reproduction subtest with 95% confidence. This exposure level associated with a 1-in-1000 risk for non-cancer neurocognitive deficits is lower than the current RfC for PCE of 0.0059 ppm, which is based on standard point of departure and uncertainty factor approaches for the same neurotoxic effects in occupationally exposed adults. We found that the population-level risk of cognitive deficit (indicating central nervous system dysfunction) is estimated to be greater than the cancer risk level of 1-in-100,000 at a similar chronic exposure level. The extension of toxicological endpoints to more clinically relevant endpoints, along with consideration of magnitude and severity of effect, will help in the selection of acceptable risk targets for non-cancer effects. We find that probabilistic approaches can 1) provide greater context to existing RfDs and RfCs by describing the probability of effect across a range of exposure levels including the RfD/RfC in a diverse population for a given magnitude of effect and confidence level, 2) relate effects of chemical exposures to clinical disease risk so that the resulting risk assessments can better inform decision-makers and benefit-cost analysis, and 3) better reflect the underlying biology and uncertainties of population risks. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Health: A Global Access Science Source is the property of BioMed Central and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Application of probabilistic methods to address variability and uncertainty in estimating risks for non-cancer health effects.
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  Data: <searchLink fieldCode="AR" term="%22Nielsen%2C+Greylin+H%2E%22">Nielsen, Greylin H.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Heiger-Bernays%2C+Wendy+J%2E%22">Heiger-Bernays, Wendy J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> whb@bu.edu</i><br /><searchLink fieldCode="AR" term="%22Levy%2C+Jonathan+I%2E%22">Levy, Jonathan I.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22White%2C+Roberta+F%2E%22">White, Roberta F.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Axelrad%2C+Daniel+A%2E%22">Axelrad, Daniel A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lam%2C+Juleen%22">Lam, Juleen</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chartres%2C+Nicholas%22">Chartres, Nicholas</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Abrahamsson%2C+Dimitri+Panagopoulos%22">Abrahamsson, Dimitri Panagopoulos</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rayasam%2C+Swati+D%2E+G%2E%22">Rayasam, Swati D. G.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shaffer%2C+Rachel+M%2E%22">Shaffer, Rachel M.</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zeise%2C+Lauren%22">Zeise, Lauren</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Woodruff%2C+Tracey+J%2E%22">Woodruff, Tracey J.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ginsberg%2C+Gary+L%2E%22">Ginsberg, Gary L.</searchLink><relatesTo>7</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Health%3A+A+Global+Access+Science+Source%22">Environmental Health: A Global Access Science Source</searchLink>. 1/12/2023, Vol. 21 Issue 1, p1-13. 13p.
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  Data: *<searchLink fieldCode="DE" term="%22Health+risk+assessment%22">Health risk assessment</searchLink><br />*<searchLink fieldCode="DE" term="%22Poisons%22">Poisons</searchLink><br /><searchLink fieldCode="DE" term="%22Estimates%22">Estimates</searchLink><br /><searchLink fieldCode="DE" term="%22Cost+effectiveness%22">Cost effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Central+nervous+system%22">Central nervous system</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Probabilistic+number+theory%22">Probabilistic number theory</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+risk+factors%22">Disease risk factors</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22United+States%2E+Environmental+Protection+Agency%22">United States. Environmental Protection Agency</searchLink>
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  Label: Abstract
  Group: Ab
  Data: Human health risk assessment currently uses the reference dose or reference concentration (RfD, RfC) approach to describe the level of exposure to chemical hazards without appreciable risk for non-cancer health effects in people. However, this "bright line" approach assumes that there is minimal risk below the RfD/RfC with some undefined level of increased risk at exposures above the RfD/RfC and has limited utility for decision-making. Rather than this dichotomous approach, non-cancer risk assessment can benefit from incorporating probabilistic methods to estimate the amount of risk across a wide range of exposures and define a risk-specific dose. We identify and review existing approaches for conducting probabilistic non-cancer risk assessments. Using perchloroethylene (PCE), a priority chemical for the U.S. Environmental Protection Agency under the Toxic Substances Control Act, we calculate risk-specific doses for the effects on cognitive deficits using probabilistic risk assessment approaches. Our probabilistic risk assessment shows that chronic exposure to 0.004 ppm PCE is associated with approximately 1-in-1,000 risk for a 5% reduced performance on the Wechsler Memory Scale Visual Reproduction subtest with 95% confidence. This exposure level associated with a 1-in-1000 risk for non-cancer neurocognitive deficits is lower than the current RfC for PCE of 0.0059 ppm, which is based on standard point of departure and uncertainty factor approaches for the same neurotoxic effects in occupationally exposed adults. We found that the population-level risk of cognitive deficit (indicating central nervous system dysfunction) is estimated to be greater than the cancer risk level of 1-in-100,000 at a similar chronic exposure level. The extension of toxicological endpoints to more clinically relevant endpoints, along with consideration of magnitude and severity of effect, will help in the selection of acceptable risk targets for non-cancer effects. We find that probabilistic approaches can 1) provide greater context to existing RfDs and RfCs by describing the probability of effect across a range of exposure levels including the RfD/RfC in a diverse population for a given magnitude of effect and confidence level, 2) relate effects of chemical exposures to clinical disease risk so that the resulting risk assessments can better inform decision-makers and benefit-cost analysis, and 3) better reflect the underlying biology and uncertainties of population risks. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Health: A Global Access Science Source is the property of BioMed Central and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1186/s12940-022-00918-z
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