Albano Giuseppina, Giorno Virginia, Román-Román Patricia, Román-Román Sergio, Torres-Ruiz Francisco
Dip. di Scienze Economiche e Statistiche, Università di Salerno, Italy.
Dip. di Studi e Ricerche Aziendali (Management and Information Technology), Università di Salerno, Italy.
J Theor Biol. 2015 Jan 7;364:206-19. doi: 10.1016/j.jtbi.2014.09.014. Epub 2014 Sep 19.
A modified Gompertz diffusion process is considered to model tumor dynamics. The infinitesimal mean of this process includes non-homogeneous terms describing the effect of therapy treatments able to modify the natural growth rate of the process. Specifically, therapies with an effect on cell growth and/or cell death are assumed to modify the birth and death parameters of the process. This paper proposes a methodology to estimate the time-dependent functions representing the effect of a therapy when one of the functions is known or can be previously estimated. This is the case of therapies that are jointly applied, when experimental data are available from either an untreated control group or from groups treated with single and combined therapies. Moreover, this procedure allows us to establish the nature (or, at least, the prevalent effect) of a single therapy in vivo. To accomplish this, we suggest a criterion based on the Kullback-Leibler divergence (or relative entropy). Some simulation studies are performed and an application to real data is presented.
考虑用一种修正的Gompertz扩散过程来模拟肿瘤动态。该过程的无穷小均值包含非齐次项,这些项描述了能够改变该过程自然生长速率的治疗效果。具体而言,假定对细胞生长和/或细胞死亡有影响的治疗会改变该过程的出生和死亡参数。本文提出了一种方法,当其中一个函数已知或可以预先估计时,用于估计代表治疗效果的时间相关函数。联合应用治疗时就是这种情况,此时可以从未经治疗的对照组或接受单一和联合治疗的组获得实验数据。此外,该程序使我们能够确定单一治疗在体内的性质(或者至少是主要效果)。为实现这一点,我们提出了一个基于Kullback-Leibler散度(或相对熵)的准则。进行了一些模拟研究并展示了对实际数据的应用。