A Web-Based System for Bayesian Benchmark Dose Estimation

Shao, Kan; Shapiro, Andrew J.

doi:10.1289/ehp1289

Cited by 101 publications

(91 citation statements)

References 26 publications

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“…Moreover, this large number of endpoints and chemicals enabled us to draw general conclusions as to the level of protection implied by current RfDs, extending previous work by Castorina and Woodruff ( 2003 ), the extent that exposure limits based on a probabilistic RfD are likely to differ from current RfDs, and what additional data or analyses could reduce uncertainty in the predicted risks. Finally, we deployed the workflow in two online tools: a standalone web app titled APROBAweb at https://wchiu.shinyapps.io/APROBAweb / ( Chiu 2018a ) and an implementation that could be integrated with Bayesian benchmark dose modeling at https://benchmarkdose.org ( Shao and Shapiro 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose–Response Assessments for Noncancer Effects

Chiu

Axelrad

Dalaijamts

et al. 2018

Environ Health Perspect

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Background:The National Academies recommended risk assessments redefine the traditional noncancer Reference Dose (RfD) as a probabilistically derived risk-specific dose, a framework for which was recently developed by the World Health Organization (WHO).Objectives:Our aim was to assess the feasibility and implications of replacing traditional RfDs with probabilistic estimates of the human dose associated with an effect magnitude M and population incidence I (HDMnormalI).Methods:We created a comprehensive, curated database of RfDs derived from animal data and developed a standardized, automated, web-accessible probabilistic dose–response workflow implementing the WHO framework.Results:We identified 1,464 RfDs and associated endpoints, representing 608 chemicals across many types of effects. Applying our standardized workflow resulted in 1,522 HDMnormalI values. Traditional RfDs are generally within an order of magnitude of the HDMnormalI lower confidence bound for I=1% and M values commonly used for benchmark doses. The greatest contributor to uncertainty was lack of benchmark dose estimates, followed by uncertainty in the extent of human variability. Exposure at the traditional RfD frequently implies an upper 95% confidence bound of several percent of the population affected. Whether such incidences are considered acceptable is likely to vary by chemical and risk context, especially given the wide range of severity of the associated effects, from clinical chemistry to mortality.Conclusions:Overall, replacing RfDs with HDMnormalI estimates can provide a more consistent, scientifically rigorous, and transparent basis for risk management decisions, as well as support additional decision contexts such as economic benefit–cost analysis, risk–risk tradeoffs, life-cycle impact analysis, and emergency response. https://doi.org/10.1289/EHP3368

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Section: Introductionmentioning

confidence: 99%

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose–Response Assessments for Noncancer Effects

Chiu

Axelrad

Dalaijamts

et al. 2018

Environ Health Perspect

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“…[45] All steps were established under the BMDS guidelines. [46][47][48][49] Multiple models were selected for analysis, including extra risk assumptions for background and a benchmark response of 5%. [33,34] According to the included studies, the dose response was divided into two categories: family economic status in childhood and childhood housing conditions.…”

Section: Quality Assessmentmentioning

confidence: 99%

Family Socioeconomic Position and Lung Cancer Risk: A Meta-analysis and a Mendelian Randomization Study

Wang¹,

Li²,

Huo³

et al. 2020

Preprint

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BackgroundFamily socioeconomic position (SEP) in childhood is an important factor to predict some chronic diseases. However, the association between family SEP in childhood and the risk of lung cancer is not clear. MethodsA systematic search was performed to explore their relationship. We selected education level, socioeconomic positions of parents and childhood housing conditions to represent an individual family SEP. Hazard ratios (HRs) of lung cancer specific-mortality were synthesized using a random effects model. Two-sample Mendelian randomization (MR) was carried out with summary data from published genome-wide association studies of SEP to assess the possible causal relationship of SEP and risk of lung cancer. ResultsThrough meta-analysis of 13 studies, we observed that poorer SEP was associated with increased lung cancer risk (HR: 1.25, 95% CI: 1.10, 1.43). In addition, the dose-response analysis revealed a negative correlation between SEP in childhood and lung cancer in adulthood. Same conclusion was reached in MR [(education level) OR 0.50, 95% CI: 0.39, 0.63; P: <0.001]. ConclusionsThis study indicates that poor family SEP in childhood is a causal risk factor for lung cancer. We believe this population may receive greater benefit from lung cancer screening programs.Systematic review registrationProspero ID: 159082

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“…Using data from Tryphonas et al (1991) (summarized in Table S9), we conducted benchmark dose modeling of decreases in immunoglobulin M. This is a sensitive end point, selected based on high statistical significance and relatively large effects reported in the study. We used the web portal benchmarkdose.org (Shao and Shapiro 2018), setting the benchmark response at 50%, a value similar to the lowest observed adverse effect-level for multiple effects reported in the study (Tryphonas et al 1991). To account for model uncertainty, we used Bayesian model averaging (three Markov Chains for eight different models) as described by Shao and Shapiro (2018).…”

Section: Dose-response and Severitymentioning

confidence: 99%

“…We used the web portal benchmarkdose.org (Shao and Shapiro 2018), setting the benchmark response at 50%, a value similar to the lowest observed adverse effect-level for multiple effects reported in the study (Tryphonas et al 1991). To account for model uncertainty, we used Bayesian model averaging (three Markov Chains for eight different models) as described by Shao and Shapiro (2018). The remaining probabilistic extrapolations were conducted following approaches described by Chiu and Slob (2015) and Chiu et al (2018).…”

Section: Dose-response and Severitymentioning

confidence: 99%

Human Health Benefits from Fish Consumption vs. Risks from Inhalation Exposures Associated with Contaminated Sediment Remediation: Dredging of the Hudson River

Kvasnicka

Stylianou

Nguyen

et al. 2019

Environ Health Perspect

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BACKGROUND: Billions of dollars are spent on environmental dredging (ED) to remediate contaminated sediments, with one goal being reduced human health risks. However, ED may increase health risks in unanticipated ways, thus potentially reducing net benefits. OBJECTIVES: To assess the ways that ED may increase health risks in unanticipated ways, thus potentially reducing net benefits, we quantitatively assessed a subset of population health benefits and risks of ED, using the 2009-2015 remediation of the Hudson River Polychlorinated Biphenyls (PCBs) Superfund Site as a case study. Three remediation scenarios were evaluated: No Action (NA), Source Control (SC), and ED. METHODS: We quantified health benefits for each scenario from reduced PCB levels in Hudson River fish, and health risks from ED operations due to increased inhalation exposures to PCBs and fine particulate matter (PM 2:5), using disability-adjusted life years (DALYs) as a common metric. Occupational health risks were also considered in a separate sensitivity analysis. Estimates of population-level benefits and risks included Monte Carlo simulation-based uncertainty analysis. RESULTS: Under NA, fish consumption would result in an estimated health burden of 112 DALYs, and ED would lead to a reduction of 15 DALYs in excess of SC. ED operations were estimated to induce a total burden of 33 DALYs, dominated by PM 2:5 impacts from rail transport emissions (32 DALYs). Including uncertainty, the net health benefit of ED ranged from-138 to + 1,326 avoided DALYs (90% confidence), with a median of-11 avoided DALYs. CONCLUSIONS: For the considered impacts, ED in the Hudson River might not have led to an overall net positive human health impact. The benefits and risks of ED, however, have different degrees of uncertainty and involve different populations. Reducing long-distance transport of dredged sediment is a priority. This comparative approach could be used prospectively to better determine trade-offs involved in different remediation scenarios and to improve remediation design to maximize benefits while minimizing risks.

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A Web-Based System for Bayesian Benchmark Dose Estimation

Cited by 101 publications

References 26 publications

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose–Response Assessments for Noncancer Effects

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose–Response Assessments for Noncancer Effects

Family Socioeconomic Position and Lung Cancer Risk: A Meta-analysis and a Mendelian Randomization Study

Human Health Benefits from Fish Consumption vs. Risks from Inhalation Exposures Associated with Contaminated Sediment Remediation: Dredging of the Hudson River

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