Evaluation of the Radiobiological Models Predicting the Radiation-Induced Hypothyroidism in the Partially Irradiated Thyroid Gland of Patients with Breast Cancer

Background: Radiation-induced hypothyroidism (RHT) is one of the side effects that might have an impact on quality life patients with breast cancer treated radiotherapy. Objectives: The aim current study was to evaluate performances Lyman-Kutcher-Burman (LKB) and Log-Logistic models in prediction (HT) as well estimation model parameters for incidence RHT among cancer. Methods: Fifty-two radiation therapy (RT) were prospectively evaluated. Patients' serum samples [tri-iodothyronine, thyroxine, thyroid-stimulating hormone (TSH), free triiodothyronine, thyroxine] measured before RT also at a regular time interval until 1 year after completion RT. For each patient, dose-volume histograms (DVHs) thyroid gland derived from their treatment planning dataset. Patients whose TSH levels higher than normal decrease FT4 considered cases RHT. LKB radiobiological evaluated by comparing them resultant follow-up data. been deduced fitting fitted Bayesian setting compared according widely applicable information criterion (WAIC). Results: Twenty-one (40%) developed end treatment. values D50 37.71 25.50 Gy, respectively partially irradiated mean obtained 6.7 months studied group. Conclusions: A volumetric effect found implemented tissue complication probability models. Compared data, ranked best predicting rate