The model muddle: in search of tumour growth laws
arXiv:1209.3170 · doi:10.1158/0008-5472.CAN-12-4355
Abstract
In this article we shall trace the historical development of tumour growth laws, which in a quantitative fashion describe the increase in tumour mass/volume over time. These models are usually formulated in terms of differential equations that relate the growth rate of the tumour to its current state, and range from the simple one-parameter exponential growth model, to more advanced models that contain a large number of parameters. Understanding the assumptions and consequences of such models is important, since they often underpin more complex models of tumour growth. The conclusion of this brief survey is that although much improvement has occurred over the last century, more effort and new models are required if we are to understand the intricacies of tumour growth.
Cited by in corpus (9)
- Classical Mathematical Models for Description and Prediction of Experimental Tumor Growth
- Universal scaling laws rule explosive growth inhuman cancers
- Innovations in Integrating Machine Learning and Agent-Based Modeling of Biomedical Systems
- Designing experimental conditions to use the Lotka-Volterra model to infer tumor cell line interaction types
- A closer look at parameter identifiability, model selection and handling of censored data with Bayesian Inference in mathematical models of tumour growth
- A mathematical model of CAR-T cell therapy in combination with chemotherapy for malignant gliomas
- Inferring Density-Dependent Population Dynamics Mechanisms through Rate Disambiguation for Logistic Birth-Death Processes
- A Seascape Origin of Richards Growth
- Uncertainty quantification and control of kinetic models of tumour growth under clinical uncertainties