Predicting resistance and pseudoprogression: are minimalistic immunoediting mathematical models capable of forecasting checkpoint inhibitor treatment outcomes in lung cancer?-Reference-Cited by-同舟云学术

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

Published:2024-10 Issue: Volume:376 Page:109287
ISSN:0025-5564
Container-title:Mathematical Biosciences
language:en
Short-container-title:Mathematical Biosciences

Author:

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

Funder

International Graduate School of Science and Engineering

DFG

Publisher

Elsevier BV

Reference67 articles.

1. Non-oncogene addicted metastatic non-small-cell lung cancer: ESMO clinical practice guideline for diagnosis, treatment and follow-up;Hendriks;Ann. Oncol.,2023

2. Global cancer statistics, 2012;Torre;CA: Cancer J. Clin.,2015

3. SEER*Explorer: An interactive website for SEER cancer statistics;Surveillance Research Program,2023

4. Acquired resistance to immune checkpoint inhibitors;Schoenfeld;Cancer Cell,2020

5. Cancer immunotherapy using checkpoint blockade;Ribas;Science,2018

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