| Popis: |
Cancer is the second most common cause of death in the US. While mathematical models are often used to predict progression of the disease and treatment outcomes, we don’t yet know how to accurately model tumor growth. Several ODE models (exponential, Mendelsohn, logistic, linear, surface, Bertalanff y, and Gompertz) have been proposed to model tumor growth. We examined the predictions of the models both for untreated growth and growth during treatment with chemotherapy. We compared the predicted maximum volume of the tumor, the doubling time, and the amount of chemotherapy needed to end tumor growth for each of the models and found that the predictions vary dramatically. This work highlights the need for detailed experiments to aid in choosing appropriate cancer growth models. |
