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Statistical Modelling
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Use of fractional polynomials for dose-response modelling and quantitative risk assessment in developmental toxicity studies

Christel Faes

Center for Statistics, Biostatistics, Limburgs Universitair Centrum, Diepenbeek, Belgium, christel.faes{at}luc.ac.be

Helena Geys

Center for Statistics, Biostatistics, Limburgs Universitair Centrum, Diepenbeek, Belgium

Marc Aerts

Center for Statistics, Biostatistics, Limburgs Universitair Centrum, Diepenbeek, Belgium

Geert Molenberghs

Center for Statistics, Biostatistics, Limburgs Universitair Centrum, Diepenbeek, Belgium

Developmental toxicity studies are designed to assess the potential adverse effects of an exposure on developing fetuses. Safe dose levels can be determined using dose-response modelling. To this end, it is important to investigate the effect of misspecifying the dose-response model on the safe dose. Since classical polynomial predictors are often of poor quality, there is a clear need for alternative specifications of the predictors, such as fractional polynomials. By means of simulations, we will show how fractional polynomial predictors may resolve possible model misspecifications and may thus yield more reliable estimates of the benchmark doses.

Key Words: benchmark dose • beta-binomial model • conditional model • developmental toxicity • dose-response • fractional polynomials

Statistical Modelling, Vol. 3, No. 2, 109-125 (2003)
DOI: 10.1191/1471082X03st051oa
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