IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v26y2006i4p1031-1043.html
   My bibliography  Save this article

Comparing Experimental Designs for Benchmark Dose Calculations for Continuous Endpoints

Author

Listed:
  • Kristi Kuljus
  • Dietrich Von Rosen
  • Salomon Sand
  • Katarina Victorin

Abstract

The BMD (benchmark dose) method that is used in risk assessment of chemical compounds was introduced by Crump (1984) and is based on dose‐response modeling. To take uncertainty in the data and model fitting into account, the lower confidence bound of the BMD estimate (BMDL) is suggested to be used as a point of departure in health risk assessments. In this article, we study how to design optimum experiments for applying the BMD method for continuous data. We exemplify our approach by considering the class of Hill models. The main aim is to study whether an increased number of dose groups and at the same time a decreased number of animals in each dose group improves conditions for estimating the benchmark dose. Since Hill models are nonlinear, the optimum design depends on the values of the unknown parameters. That is why we consider Bayesian designs and assume that the parameter vector has a prior distribution. A natural design criterion is to minimize the expected variance of the BMD estimator. We present an example where we calculate the value of the design criterion for several designs and try to find out how the number of dose groups, the number of animals in the dose groups, and the choice of doses affects this value for different Hill curves. It follows from our calculations that to avoid the risk of unfavorable dose placements, it is good to use designs with more than four dose groups. We can also conclude that any additional information about the expected dose‐response curve, e.g., information obtained from studies made in the past, should be taken into account when planning a study because it can improve the design.

Suggested Citation

  • Kristi Kuljus & Dietrich Von Rosen & Salomon Sand & Katarina Victorin, 2006. "Comparing Experimental Designs for Benchmark Dose Calculations for Continuous Endpoints," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 1031-1043, August.
    • Handle: RePEc:wly:riskan:v:26:y:2006:i:4:p:1031-1043
    DOI: 10.1111/j.1539-6924.2006.00798.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2006.00798.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1539-6924.2006.00798.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. W. Slob & M. N. Pieters, 1998. "A Probabilistic Approach for Deriving Acceptable Human Intake Limits and Human Health Risks from Toxicological Studies: General Framework," Risk Analysis, John Wiley & Sons, vol. 18(6), pages 787-798, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fereshteh Kalantari & Joakim Ringblom & Salomon Sand & Mattias Öberg, 2017. "Influence of Distribution of Animals between Dose Groups on Estimated Benchmark Dose and Animal Distress for Quantal Responses," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1716-1728, September.
    2. Joakim Ringblom & Fereshteh Kalantari & Gunnar Johanson & Mattias Öberg, 2018. "Influence of Distribution of Animals between Dose Groups on Estimated Benchmark Dose and Animal Welfare for Continuous Effects," Risk Analysis, John Wiley & Sons, vol. 38(6), pages 1143-1153, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Mirjam Moerbeek & Aldert H. Piersma & Wout Slob, 2004. "A Comparison of Three Methods for Calculating Confidence Intervals for the Benchmark Dose," Risk Analysis, John Wiley & Sons, vol. 24(1), pages 31-40, February.
    3. Kan Shao & Jeffrey S. Gift, 2014. "Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 101-120, January.
    4. Salomon J. Sand & Dietrich Von Rosen & Agneta Falk Filipsson, 2003. "Benchmark Calculations in Risk Assessment Using Continuous Dose‐Response Information: The Influence of Variance and the Determination of a Cut‐Off Value," Risk Analysis, John Wiley & Sons, vol. 23(5), pages 1059-1068, October.
    5. Katsuyuki Murata & Esben Budtz‐Jørgensen & Philippe Grandjean, 2002. "Benchmark Dose Calculations for Methylmercury‐Associated Delays on Evoked Potential Latencies in Two Cohorts of Children," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 465-474, June.
    6. Zi-Fan Yu & Paul J. Catalano, 2005. "Quantitative Risk Assessment for Multivariate Continuous Outcomes with Application to Neurotoxicology: The Bivariate Case," Biometrics, The International Biometric Society, vol. 61(3), pages 757-766, September.
    7. Walter W. Piegorsch, 2010. "Translational benchmark risk analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 13(5), pages 653-667, July.
    8. Roger Cooke, 2010. "Conundrums with Uncertainty Factors," Risk Analysis, John Wiley & Sons, vol. 30(3), pages 330-339, March.
    9. Kenny S. Grump & Tord Kjellström & Annette M. Shipp & Abraham Silvers & Alistair Stewart, 1998. "Influence of Prenatal Mercury Exposure Upon Scholastic and Psychologica Test Performance: Benchmark Analysis of a New Zealand Cohort," Risk Analysis, John Wiley & Sons, vol. 18(6), pages 701-713, December.
    10. 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.
    11. Hilko Van Der Voet & Wout Slob, 2007. "Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization," Risk Analysis, John Wiley & Sons, vol. 27(2), pages 351-371, April.
    12. Walter W. Piegorsch & Hui Xiong & Rabi N. Bhattacharya & Lizhen Lin, 2014. "Benchmark Dose Analysis via Nonparametric Regression Modeling," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 135-151, January.
    13. Susan Dekkers & Jan Telman & Monique A. J. Rennen & Marco J. Appel & Cees De Heer, 2006. "Within‐Animal Variation as an Indication of the Minimal Magnitude of the Critical Effect Size for Continuous Toxicological Parameters Applicable in the Benchmark Dose Approach," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 867-880, August.
    14. Mirjana Glisovic‐Bensa & Walter W. Piegorsch & Edward J. Bedrick, 2024. "Bayesian benchmark dose risk assessment with mixed‐factor quantal data," Environmetrics, John Wiley & Sons, Ltd., vol. 35(5), August.
    15. Steven B. Kim & Ralph L. Kodell & Hojin Moon, 2014. "A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 453-464, March.
    16. Walter W. Piegorsch & R. Webster West, 2005. "Benchmark Analysis: Shopping with Proper Confidence," Risk Analysis, John Wiley & Sons, vol. 25(4), pages 913-920, August.
    17. 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.
    18. Wouter Fransman & Harrie Buist & Eelco Kuijpers & Tobias Walser & David Meyer & Esther Zondervan‐van den Beuken & Joost Westerhout & Rinke H. Klein Entink & Derk H. Brouwer, 2017. "Comparative Human Health Impact Assessment of Engineered Nanomaterials in the Framework of Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 37(7), pages 1358-1374, July.
    19. Matteo Goldoni & Maria Vittoria Vettori & Rossella Alinovi & Andrea Caglieri & Sandra Ceccatelli & Antonio Mutti, 2003. "Models of Neurotoxicity: Extrapolation of Benchmark Doses in Vitro," Risk Analysis, John Wiley & Sons, vol. 23(3), pages 505-514, June.
    20. Hoda Izadi & Jean E. Grundy & Ranjan Bose, 2012. "Evaluation of the Benchmark Dose for Point of Departure Determination for a Variety of Chemical Classes in Applied Regulatory Settings," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 830-835, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:26:y:2006:i:4:p:1031-1043. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.