Computational modeling study demonstrates individual tumor burden quantification under chemo-immunotherapy in non-small cell lung cancer, suggesting earlier therapy optimization at diagnosis.
The mathematical model presented in this study gives insights in how this could be achieved, taking into account different treatment possibilities and therefore being able to compare therapy schedules for individual patients with different clinical parameters. The framework was tested on three patients with non-small cell lung cancer, one of the deadliest types of cancer worldwide, and clinical history including platinum-based chemotherapy and PD-L1-targeted immunotherapy. Results yield promising insights into the framework to establish methods to quantify effects of different therapy methods and prognostic features for individual patients already at stage of primary diagnosis.
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Schlicke et al. (2021) studied this question.
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