Predictive scores for the development of autoimmune thyroid diseases

Abstract

Introduction. Modern medicine should be predictive, preventive, personalized, participatory. Predictive models can be helpful in predicting the course of a disease, screening undiagnosed individuals, and estimating the effectiveness of treatment. Purpose. Adaptation and practical implementation of predictive scores for the development of autoimmune thyroid disease (ATD). Material and methods. Systematization of information on predictive scores in autoimmune thyroid diseases was carried out. Results. Thyroperoxidase antibody titer, TSH level, heredity were determined as independent factors for the development of ATD. Low THEA predictive score means a low risk of developing ATD in the next 5 years (tabel. 1). GREAT score is based on clinical parameters at the time of diagnosis of Graves' disease and is easy to apply in clinical practice. A 25% risk of recurrence favors medical treatment and a 75% risk of recurrence – thyroid gland ablation. PREDIGO score highlights the predictive factors for endocrine ophthalmopathy (EO) (tabel. 2). The high negative predictive value allows identification of patients with minimal probability of EO occurrence. Conclusions. Prediction models can predict the development of a disease, detect undiagnosed patients, estimate the effectiveness of treatment, contribute to better decision making.