体内肿瘤生长速率的估计
Estimating Tumor Growth Rates In Vivo.
作者信息
Talkington Anne, Durrett Rick
出版信息
Bull Math Biol. 2015 Oct;77(10):1934-54. doi: 10.1007/s11538-015-0110-8.
Abstract
In this paper, we develop methods for inferring tumor growth rates from the observation of tumor volumes at two time points. We fit power law, exponential, Gompertz, and Spratt’s generalized logistic model to five data sets. Though the data sets are small and there are biases due to the way the samples were ascertained, there is a clear sign of exponential growth for the breast and liver cancers, and a 2/3’s power law (surface growth) for the two neurological cancers.
摘要
在本文中，我们开发了从两个时间点的肿瘤体积观测值推断肿瘤生长速率的方法。我们将幂律、指数、冈珀茨和斯普拉特广义逻辑模型应用于五个数据集。尽管数据集规模较小，且由于样本确定方式存在偏差，但乳腺癌和肝癌有明显的指数增长迹象，两种神经癌呈现2/3幂律（表面生长）。
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