Understanding health-related quality of life (HRQoL) dynamics is essential for assessing and improving treatment experiences; however, clinical and observational studies struggle to capture their full complexity. We use simulation modeling and the case of Chimeric Antigen Receptor T-cell therapy-a type of cancer immunotherapy that can prolong survival, but carries life-threatening risks-to study HRQoL dynamics. We developed an exploratory system dynamics model with mathematical equations and parameter values informed by literature and expert insights. We refined its feedback structure and evaluated its dynamic behavior through iterative interviews. Model simulated HRQoL from treatment approval through six months post-infusion.
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