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Modeling Fetal Death and Malformation in Developmental Toxicity Studies

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  • Paul Catalano
  • Louise Ryan
  • Daniel Scharfstein

Abstract

We review approaches to dose‐response modeling and risk assessment for binary data from developmental toxicity studies. In particular, we focus on jointly modeling fetal death and malformation and use a continuation ratio formulation of the multinomial distribution to provide a model for risk. Generalized estimating equations are used to account for clustering of animals within litters. The fitted model is then used to calculate doses corresponding to a specified level of excess risk. Two methods of arriving at a lower confidence limit or Benchmark dose are illustrated and compared. We also discuss models based on single binary end points and compare our approach to a binary analysis of whether or not the animal was ‘affected’ (either dead or malformed). The models are illustrated using data from four developmental toxicity studies in EG, DEHP, TGDM, and DYME conducted through the National Toxicology Program.

Suggested Citation

  • Paul Catalano & Louise Ryan & Daniel Scharfstein, 1994. "Modeling Fetal Death and Malformation in Developmental Toxicity Studies," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 629-637, August.
    • Handle: RePEc:wly:riskan:v:14:y:1994:i:4:p:629-637
    DOI: 10.1111/j.1539-6924.1994.tb00276.x
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    References listed on IDEAS

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    1. Louise Ryan, 1992. "The Use of Generalized Estimating Equations for Risk Assessment in Developmental Toxicity," Risk Analysis, John Wiley & Sons, vol. 12(3), pages 439-447, September.
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    Cited by:

    1. Faes, Christel & Geys, Helena & Aerts, Marc & Molenberghs, Geert, 2006. "A hierarchical modeling approach for risk assessment in developmental toxicity studies," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1848-1861, December.
    2. Meredith M. Regan & Paul J. Catalano, 1999. "Likelihood Models for Clustered Binary and Continuous Out comes: Application to Developmental Toxicology," Biometrics, The International Biometric Society, vol. 55(3), pages 760-768, September.
    3. Brent A. Coull & Alan Agresti, 2000. "Random Effects Modeling of Multiple Binomial Responses Using the Multivariate Binomial Logit-Normal Distribution," Biometrics, The International Biometric Society, vol. 56(1), pages 73-80, March.

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