Abstract:Papillary thyroid carcinoma (PTC) is the most common type of thyroid malignancy. Although most patients have a favorable prognosis, a proportion still develop locoregional recurrence or distant metastasis after initial treatment, which adversely affects long-term outcomes and quality of life. Conventional risk stratification systems based on clinicopathological features have limited ability in individualized recurrence prediction, prompting increasing interest in biomarker-based precision assessment. In recent years, substantial advances have been achieved in serological biomarkers, genetic alterations, tumor microenvironment-related immune markers, and liquid biopsy technologies. Among them, BRAFV600E mutation, TERT promoter mutation, inflammation-related indicators, and circulating tumor-derived components have demonstrated promising value in recurrence risk evaluation. Meanwhile, the integration of multi-omics approaches and artificial intelligence has further promoted the transition from single-parameter prediction to multidimensional dynamic risk models. This review summarizes the current progress in biomarkers associated with PTC recurrence risk, discusses their underlying mechanisms, clinical applications, and existing limitations, and further explores emerging strategies, including liquid biopsy, multi-omics integration, and artificial intelligence. These advances may facilitate precise risk stratification and individualized management of patients with PTC.