Predicting resistance and pseudoprogression: are minimalistic immunoediting mathematical models capable of forecasting checkpoint inhibitor treatment outcomes in lung cancer?

DOI10.1016/j.mbs.2024.109287MaRDI QIDQ6632662

Folker Schneller, Pirmin Schlicke, Kevin Robert Scibilia, Christina Kuttler

Publication date: 5 November 2024

Published in: Mathematical Biosciences (Search for Journal in Brave)

zbMATH Keywords

immunoeditingmathematical oncologydigital twinsimmunoevasionimmunoresistancetherapy outcome prediction

Mathematics Subject Classification ID

Pathology, pathophysiology (92C32)

Cites Work

• Nonlinear dynamics of immunogenic tumors: Parameter estimation and global bifurcation analysis
• Can the Kuznetsov model replicate and predict cancer growth in humans?
• The contribution of evolutionary game theory to understanding and treating cancer
• Interactions between the immune system and cancer: A brief review of non-spatial mathematical models
• Modeling tumor regrowth and immunotherapy
• Predicting radiotherapy patient outcomes with real-time clinical data using mathematical modelling

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