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Estimating a non-homogeneous Gompertz process with jumps as model of tumor dynamics

Virginia Giorno, Patricia Román-Román, Serena Spina and Francisco Torres-Ruiz

Computational Statistics & Data Analysis, 2017, vol. 107, issue C, 18-31

Abstract: A non-homogeneous stochastic model based on a Gompertz-type diffusion process with jumps is proposed to describe the evolution of a solid tumor subject to an intermittent therapeutic program. Each therapeutic application, represented by a jump in the process, instantly reduces the tumor size to a fixed value and, simultaneously, increases the growth rate of the model to represent the toxicity of the therapy. This effect is described by introducing a time-dependent function in the drift of the process. The resulting model is a combination of several non-homogeneous diffusion processes characterized by different drifts, whose transition probability density function and main characteristics are studied. The study of the model is performed by distinguishing whether the therapeutic instances are fixed in advance or guided by a strategy based on the mean of the first-passage-time through a control threshold. Simulation studies are carried out for different choices of the parameters and time-dependent functions involved.

Keywords: Non-homogeneous Gompertz diffusion process; Therapeutic application; Intermittent therapy; First-passage-time; Inference (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:107:y:2017:i:c:p:18-31

DOI: 10.1016/j.csda.2016.10.005

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