Murphy2016 - Differences in predictions of ODE models of tumor growth

Murphy2016 - Differences in predictions of
ODE models of tumor growth
Comparison of 7 ODE models for tumour
size. This models have been compared to experimental data.

This model is described in the article:

Differences in predictions
of ODE models of tumor growth: a cautionary example.

Murphy H, Jaafari H, Dobrovolny
HM.
BMC Cancer 2016 Feb; 16: 163
Abstract:

While mathematical models are often used to predict
progression of cancer and treatment outcomes, there is still
uncertainty over how to best model tumor growth. Seven ordinary
differential equation (ODE) models of tumor growth
(exponential, Mendelsohn, logistic, linear, surface, Gompertz,
and Bertalanffy) have been proposed, but there is no clear
guidance on how to choose the most appropriate model for a
particular cancer.We examined all seven of the previously
proposed ODE models in the presence and absence of
chemotherapy. We derived equations for the maximum tumor size,
doubling time, and the minimum amount of chemotherapy needed to
suppress the tumor and used a sample data set to compare how
these quantities differ based on choice of growth model.We find
that there is a 12-fold difference in predicting doubling times
and a 6-fold difference in the predicted amount of chemotherapy
needed for suppression depending on which growth model was
used.Our results highlight the need for careful consideration
of model assumptions when developing mathematical models for
use in cancer treatment planning.

This model is hosted on
BioModels Database
and identified by:
BIOMD0000000671.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.

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