TY  - JOUR
AU  - El Wajeh, Mohammad
AU  - Jung, Falco
AU  - Bongartz, Dominik
AU  - Kappatou, Chrysoula Dimitra
AU  - Ghaffari Laleh, Narmin
AU  - Mitsos, Alexander
AU  - Kather, Jakob Nikolas
TI  - Can the Kuznetsov Model Replicate and Predict Cancer Growth in Humans?
JO  - Bulletin of mathematical biology
VL  - 84
IS  - 11
SN  - 0007-4985
CY  - Heidelberg [u.a.]
PB  - Springer
M1  - FZJ-2023-00753
SP  - 130
PY  - 2022
AB  - Several mathematical models to predict tumor growth over time have been developed in the last decades. A central aspect of such models is the interaction of tumor cells with immune effector cells. The Kuznetsov model (Kuznetsov et al. in Bull Math Biol 56(2):295–321, 1994) is the most prominent of these models and has been used as a basis for many other related models and theoretical studies. However, none of these models have been validated with large-scale real-world data of human patients treated with cancer immunotherapy. In addition, parameter estimation of these models remains a major bottleneck on the way to model-based and data-driven medical treatment. In this study, we quantitatively fit Kuznetsov’s model to a large dataset of 1472 patients, of which 210 patients have more than six data points, by estimating the model parameters of each patient individually. We also conduct a global practical identifiability analysis for the estimated parameters. We thus demonstrate that several combinations of parameter values could lead to accurate data fitting. This opens the potential for global parameter estimation of the model, in which the values of all or some parameters are fixed for all patients. Furthermore, by omitting the last two or three data points, we show that the model can be extrapolated and predict future tumor dynamics. This paves the way for a more clinically relevant application of mathematical tumor modeling, in which the treatment strategy could be adjusted in advance according to the model’s future predictions.
LB  - PUB:(DE-HGF)16
C6  - 36175705
UR  - <Go to ISI:>//WOS:000861883700001
DO  - DOI:10.1007/s11538-022-01075-7
UR  - https://juser.fz-juelich.de/record/917551
ER  -