A Mechanistic Dynamic Surrogate Framework for Personalized Radioactive Iodine Therapy in Metastatic Thyroid Cancer
Résumé
Background/Objectives: Radioactive iodine (RAI) therapy is widely used to treat metastatic differentiated thyroid cancer. To investigate physiological determinants of treatment response, a mechanistic model was developed, formulated as a system of coupled ordinary differential equations. Methods: The model captures the interactions between tumor burden, thyroglobulin (T g ) production and clearance, and radioactive iodine activity within a pharmacokinetic-pharmacodynamic framework. Model parameters were estimated using the Monte Carlo Stochastic Approximation Expectation-Maximization (MCMCSAEM) algorithm, based on clinical data from a cohort of 50 patients. Results: Tumor radiosensitivity (ρ) and initial tumor burden (N 0 ) consistently emerged as the most influential factors in both responder and non-responder groups classified by disease doubling time under RAI (T d ). A reduced model using only these two parameters preserved the principal response patterns of the full model. Other parameters influenced transient dynamics but had limited effect on overall T g variance. Conclusions: These results support the use of a reduced calibration approach focused on ρ, N 0 , and the effective doubling time T d . The findings establish a theoretical foundation for developing tractable dynamic surrogates that reproduce the main treatment kinetics and support model-based clinical decision-making in RAI therapy.
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