Abstract

Controlling the number of tumor cells leads us to expect more efficient strategies for treatment of tumor. Towards this goal, a tumor-immune model with state-dependent impulsive treatments is established. This model may give an efficient treatment schedule to control tumor’s abnormal growth. By using the Poincaré map and analogue of Poincaré criterion, some conditions for the existence and stability of a positive order-1 periodic solution of this model are obtained. Moreover, we carry out numerical simulations to illustrate the feasibility of our main results and compare fixed-time impulsive treatment effects with state-dependent impulsive treatment effects. The results of our simulations say that, in determining optimal treatment timing, the model with state-dependent impulsive control is more efficient than that with fixed-time impulsive control.

Highlights

  • Cancer is a class of diseases characterized by out of control cell growth

  • The first result is on the existence of a positive order-1 periodic solution for model (4)

  • We investigate a tumor-immune model with state-dependent impulsive immunotherapy and chemotherapy

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Summary

Introduction

Cancer is a class of diseases characterized by out of control cell growth. Abnormal cells divide without control and are able to invade other tissues. Cancer is a leading cause of death worldwide. Doctors are trying to cure cancer but it has been difficult. Among many treatments for cancer, immunotherapy is a treatment method by using immune system in a body to fight cancer cells. Immune system recognizes cancer cells and leads to destruction of cancer cells before cancer cells are big enough to see. Since the mechanism of immune system in the body is very complex, it is difficult to find an efficient treatment schedule to eradicate some cancers. In order to find such schedule, a mathematical model describing dynamics of tumor-immune interactions would provide a new strategy for treatment of cancer

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