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Flexible estimates of tumour incidence for intermediately lethal tumours in a typical long-term animal bioassay
Authors:Helen Parise  Gregg E Dinse  & Louise M Ryan
Institution:Harvard School of Public Health, Boston, USA,;National Institute of Environmental Health Sciences, Research Triangle Park, USA,;Harvard School of Public Health and Dana-Farber Cancer Institute, Boston, USA
Abstract:The estimation of the incidence of tumours in an animal carcinogenicity study is complicated by the occult nature of the tumours involved (i.e. tumours are not observable before an animal's death). Also, the lethality of tumours is generally unknown, making the tumour incidence function non-identifiable without interim sacrifices, cause-of-death data or modelling assumptions. Although Kaplan–Meier curves for overall survival are typically displayed, obtaining analogous plots for tumour incidence generally requires fairly elaborate model fitting. We present a case-study of tetrafluoroethylene to illustrate a simple method for estimating the incidence of tumours as a function of more easily estimable components. One of the components, tumour prevalence, is modelled by using a generalized additive model, which leads to estimates that are more flexible than those derived under the usual parametric models. A multiplicative assumption for tumour lethality allows for the incorporation of concomitant information, such as the size of tumours. Our approach requires only terminal sacrifice data although additional sacrifice data are easily accommodated. Simulations are used to illustrate the estimator proposed and to evaluate its properties. The method also yields a simple summary measure of tumour lethality, which can be helpful in interpreting the results of a study.
Keywords:Carcinogenicity experiments  Local polynomial  Tumour prevalence
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