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Use of Mechanistic Models to Estimate Low‐Dose Cancer Risks

机译:使用机制模型估计低剂量癌症风险

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The utility of mechanistic models of cancer for predicting cancer risks at low doses is examined. Based upon a general approximation to the dose‐response that is valid at low doses, it is shown that at low doses the dose‐response predicted by a mechanistic model is a linear combination of the dose‐responses for each of the physiological parameters in the model that are affected by exposure. This demonstrates that, unless the mechanistic model provides a theoretical basis for determining the dose‐responses for these parameters, the extrapolation of risks to low doses using a mechanistic model is basically “curve fitting,” just as is the case when extrapolating using statistical models. This suggests that experiments to generate data for use in mechanistic models should emphasize measuring the dose‐response for dose‐related parameters as accurately as possible and at the lowest
机译:研究了癌症机制模型在预测低剂量癌症风险方面的效用。基于对低剂量下有效的剂量反应的一般近似,表明在低剂量下,机理模型预测的剂量反应是模型中受暴露影响的每个生理参数的剂量反应的线性组合。这表明,除非机理模型为确定这些参数的剂量反应提供理论基础,否则使用机理模型将风险外推到低剂量基本上是“曲线拟合”,就像使用统计模型外推时的情况一样。这表明,生成用于机理模型的数据的实验应强调尽可能准确地测量剂量相关参数的剂量反应

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