DEVELOPMENT AND VALIDATION OF A LOGISTIC PREDICTION MODEL FOR PAPILLARY THYROID CARCINOMA BASED ON CLINICAL AND ULTRASOUND PARAMETERS

Abstract

Early identification of papillary thyroid carcinoma (PTC) remains one of the major challenges in endocrine oncology. Although thyroid ultrasonography and fine-needle aspiration biopsy are widely used, the diagnostic accuracy of individual methods may be limited, particularly in patients with coexisting autoimmune thyroiditis or indeterminate sonographic findings. Multivariable prediction models integrating clinical and imaging characteristics may improve individualized risk assessment and facilitate clinical decision-making.