Determining Risks to Background Arsenic Using a Margin – of – Exposure Approach Presentation at Society of Risk Analysis, New England Chapter Barbara D.

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Presentation transcript:

Determining Risks to Background Arsenic Using a Margin – of – Exposure Approach Presentation at Society of Risk Analysis, New England Chapter Barbara D. Beck, Ph.D., DABT, FATS Gradient Corporation January 23, 2008

How Can Epidemiology be Used to Inform the Understanding of Background Risks from Inorganic Arsenic? Multiple opportunities, e.g. Multiple opportunities, e.g. Identification of plausible “No Observed Effect Level” for carcinogenicity Identification of plausible “No Observed Effect Level” for carcinogenicity Intake distributions, e.g. from food Intake distributions, e.g. from food Host factors that modify carcinogenicity Host factors that modify carcinogenicity Evaluating plausibility of modeled dose estimates through use of urine arsenic population studies Evaluating plausibility of modeled dose estimates through use of urine arsenic population studies Understanding the relationship between arsenic metabolism and disease Understanding the relationship between arsenic metabolism and disease

Background Ingestion of inorganic arsenic (As i ) Ingestion of inorganic arsenic (As i ) Associated with skin, bladder, and lung cancer Associated with skin, bladder, and lung cancer Studies demonstrating carcinogenicity – Taiwan, Bangladesh, Inner Mongolia, etc. Studies demonstrating carcinogenicity – Taiwan, Bangladesh, Inner Mongolia, etc. Relatively high exposures, frequently in poorly nourished populations Relatively high exposures, frequently in poorly nourished populations No confirmed association in US populations No confirmed association in US populations Challenges in developing animal model of As i carcinogenesis Challenges in developing animal model of As i carcinogenesis

Background (cont’d) Prior risk assessments Prior risk assessments Cancer Slope Factors (CSFs) range from 1.5 to 23 (mg/kg-d) -1 Cancer Slope Factors (CSFs) range from 1.5 to 23 (mg/kg-d) -1 All based on Taiwan data All based on Taiwan data Different cancer types (skin, bladder, lung), absolute vs. relative risk models, etc. Different cancer types (skin, bladder, lung), absolute vs. relative risk models, etc. All assume low dose linearity All assume low dose linearity

Identification of NOEL Cancer Data from Taiwan Figure from: Lamm, SH; Engel, A; Penn, CA; Chen, R; Feinleib, M. January 13, "Arsenic cancer risk factor in SW Taiwan dataset." Environ. Health Perspect. 39p.

Analysis of Taiwan Data by Township ◊ = Townships 2, 4, 6 □ = Townships 0, 3, 5 Figure from: Lamm, SH; Engel, A; Penn, CA; Chen, R; Feinleib, M “Arsenic cancer risk confounder in southwest Taiwan data set.” Environ. Health Perspect. 114:

Analysis of Taiwan Data by Township Suggests high background of bladder and lung cancer in townships 0, 3, 5 Suggests high background of bladder and lung cancer in townships 0, 3, 5 Clear dose-response only in in townships 2, 4, 6 Clear dose-response only in in townships 2, 4, 6 SMR > 100 at median H 2 O concentrations > 150 µg/L (CI = µg/L) SMR > 100 at median H 2 O concentrations > 150 µg/L (CI = µg/L)

Implications Offers alternate approach to LNT for evaluating cancer risks from ingestion of inorganic arsenic Offers alternate approach to LNT for evaluating cancer risks from ingestion of inorganic arsenic Determine the “No Effect” Drinking Water Level based on epidemiological data and convert to a dose Determine the “No Effect” Drinking Water Level based on epidemiological data and convert to a dose Equivalent to mg/kg-d (  “NOEL”) Equivalent to mg/kg-d (  “NOEL”) Use Margin of Exposure (MOE) to compare population dose to NOEL Use Margin of Exposure (MOE) to compare population dose to NOEL Approach compatible with US EPA cancer guidelines and current understanding of arsenic mode of action Approach compatible with US EPA cancer guidelines and current understanding of arsenic mode of action

Monte Carlo Exposure Analysis for US Populations 3 main sources for background exposure 3 main sources for background exposure Diet Diet Water Water Soil Soil Intake estimates based on population surveys Intake estimates based on population surveys

Drinking Water Key Input Distributions ParameterGMGSD95 th % As Concentrations in Drinking Water (µg/L) Groundwater Surface Water Drinking Water Intake (L/day) Child Adult

Soil Key Input Distributions ParameterGMGSD95 th % Soil Intake (mg/L) Groundwater Surface Water As Concentration in Soil (mg/kg) Child Bioavailability Vertices at 0.01, 0.16, 0.5

Food Key Input Distributions ParameterGMGSD95 th % Dietary Intake (µg/kg-day) Child (1 to 6 years) Adult

Summary of Results of Probabilistic Exposure Analysis

Intake at 50 th Percentile

Use of Epidemiology to Evaluate Plausibility of Intakes 50 th percentile = 7.1 x mg/kg-d 50 th percentile = 7.1 x mg/kg-d Can convert to potential urine concentration Can convert to potential urine concentration 70kg 70kg 0.8 – 2 L urine/day 0.8 – 2 L urine/day 100% excreted in urine (our estimate) 100% excreted in urine (our estimate) = ~ 2.5 to 6.2 µg arsenic/L urine = ~ 2.5 to 6.2 µg arsenic/L urine Comparable to 7.5 µg/L median from Kalman Comparable to 7.5 µg/L median from Kalman

Risk Calculation Results Mean5 th Percentile 50 th Percentile 95 th Percentile MOE Estimate a LICR Estimate – Based on IRIS CSF b of x x x x LICR Estimate – Based on Alternative Value c of x x x x Notes: a – MOE calculation based on Point of Departure Value of mg/kg-day b – Calculation based on CSF value presented in EPA’s IRIS database: 1.5 (mg/kg-day) -1 c – Calculation based on alternative CSF value used in recent EPA risk assessments: 3.67 (mg/kg-day) -1

Implication of Analysis Choice of dose-response model critical Choice of dose-response model critical 95 th percentile risks exceed permissible criteria using recent CSF, based on LNT 95 th percentile risks exceed permissible criteria using recent CSF, based on LNT 95 th percentile risks do not exceed criteria using epidemiologically-based NOEL 95 th percentile risks do not exceed criteria using epidemiologically-based NOEL

Sensitivity Analysis Use of alternate assumptions Use of alternate assumptions Increased or decreased intake from each medium by 50% Increased or decreased intake from each medium by 50% Greatest impact was change in adult dietary intake Greatest impact was change in adult dietary intake Changed Average Lifetime Daily Dose by +/- 23% Changed Average Lifetime Daily Dose by +/- 23%

Sensitivity Analysis (cont’d) Uncertainty in NOEL Uncertainty in NOEL Use of lower confidence unit on dose of 42 µg/L (instead of 150 µg/L) Use of lower confidence unit on dose of 42 µg/L (instead of 150 µg/L) 95 th percentile MOE – 19 (versus 58) 95 th percentile MOE – 19 (versus 58) Estimates of NOEL based on different diet and water intakes in Taiwan – more “restrictive” NOELs, MOEs all > 13 Estimates of NOEL based on different diet and water intakes in Taiwan – more “restrictive” NOELs, MOEs all > 13

Implications Use of epidemiological data to assess risks of ingestion of inorganic arsenic -- informative on multiple levels Use of epidemiological data to assess risks of ingestion of inorganic arsenic -- informative on multiple levels Toxicity quantification Toxicity quantification Exposure assumptions Exposure assumptions Plausibility of results Plausibility of results