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Benchmark dose risk analysis with mixed‐factor quantal data in environmental risk assessment

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  • Maria A. Sans‐Fuentes
  • Walter W. Piegorsch

Abstract

Benchmark analysis is a general risk estimation strategy for identifying the benchmark dose (BMD) past which the risk of exhibiting an adverse environmental response exceeds a fixed, target value of benchmark response. Estimation of BMD and of its lower confidence limit (BMDL) is well understood for the case of an adverse response to a single stimulus. In many environmental settings, however, one or more additional, secondary, qualitative factor(s) may collude to affect the adverse outcome, such that the risk changes with differential levels of the secondary factor. This article extends the single‐dose BMD paradigm to a mixed‐factor setting with a secondary qualitative factor possessing two levels. With focus on quantal‐response data and using a generalized linear model with a complementary‐log link function, we derive expressions for BMD and BMDL. We study the operating characteristics of six different multiplicity‐adjusted approaches to calculate the BMDL, using Monte Carlo evaluations. We illustrate the calculations via an example dataset from environmental carcinogenicity testing.

Suggested Citation

  • Maria A. Sans‐Fuentes & Walter W. Piegorsch, 2021. "Benchmark dose risk analysis with mixed‐factor quantal data in environmental risk assessment," Environmetrics, John Wiley & Sons, Ltd., vol. 32(5), August.
    • Handle: RePEc:wly:envmet:v:32:y:2021:i:5:n:e2677
    DOI: 10.1002/env.2677
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    References listed on IDEAS

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    1. Kenny S. Crump, 1995. "Calculation of Benchmark Doses from Continuous Data," Risk Analysis, John Wiley & Sons, vol. 15(1), pages 79-89, February.
    2. Walter W. Piegorsch & Lingling An & Alissa A. Wickens & R. Webster West & Edsel A. Peña & Wensong Wu, 2013. "Information‐theoretic model‐averaged benchmark dose analysis in environmental risk assessment," Environmetrics, John Wiley & Sons, Ltd., vol. 24(3), pages 143-157, May.
    3. Signe M. Jensen & Felix M. Kluxen & Christian Ritz, 2019. "A Review of Recent Advances in Benchmark Dose Methodology," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2295-2315, October.
    4. Roland C. Deutsch & Walter W. Piegorsch, 2012. "Benchmark Dose Profiles for Joint-Action Quantal Data in Quantitative Risk Assessment," Biometrics, The International Biometric Society, vol. 68(4), pages 1313-1322, December.
    5. Edsel A. Peña & Wensong Wu & Walter Piegorsch & Ronald W. West & LingLing An, 2017. "Model Selection and Estimation with Quantal‐Response Data in Benchmark Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 716-732, April.
    6. Lelys Bravo Guenni & Susan J. Simmons & R. Webster West & Walter W. Piegorsch & Edsel A. Peña & Lingling An & Wensong Wu & Alissa A. Wickens & Hui Xiong & Wenhai Chen, 2012. "The impact of model uncertainty on benchmark dose estimation," Environmetrics, John Wiley & Sons, Ltd., vol. 23(8), pages 706-716, December.
    7. Matthew W. Wheeler & A. John Bailer & Tarah Cole & Robert M. Park & Kan Shao, 2017. "Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2107-2118, November.
    8. Antonio Canale & Daniele Durante & David B. Dunson, 2018. "Convex mixture regression for quantitative risk assessment," Biometrics, The International Biometric Society, vol. 74(4), pages 1331-1340, December.
    9. Naha J. Farhat & Edward L. Boone & David J. Edwards, 2020. "A new method for determining the benchmark dose tolerable region and endpoint probabilities for toxicology experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(5), pages 775-803, April.
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