Integrating shear wave elastography into clinical prediction of Graves' disease recurrence: a novel risk scoring system.

Objective: This study aims to evaluate the utility of shear wave elastography (SWE) in predicting the recurrence risk of Graves' disease(GD), to construct a recurrence risk prediction model that integrates SWE and clinical characteristics, and to develop a risk scoring system aimed at enhancing the survival rate of patients with GD following drug treatment and prognosis management.

Methods: A prospective cohort study was conducted involving with 169 patients diagnosed with first-episode GD. By analyzing SWE parameters, three-dimensional thyroid volume, TRAb levels, and other clinical indicators, the Cox proportional hazards model was used to construct a recurrence risk prediction model for GD. Bootstrap resampling was employed to verify the model's reliability. A simple recurrence risk scoring system was also developed based on independent risk factors for clinical use.

Results: The study identified several factors significantly associated with GD recurrence: age <35 years, a family history of GD, an initial TRAb level≧15 IU/ml, a thyroid volume≧19 cm³, an initial SWE≧2.0 m/s, and a TSH(thyroid stimulating hormone) normalization duration <4 months. Notably, SWE was found to be a strong predictor, with patients exhibiting SWE ≥2.0 m/s having a recurrence risk that is 4.54 times greater than those with lower values. Based on these risk factors, a scoring system was developed with a cutoff of 4 points for recurrence risk, demonstrating a sensitivity of 74% and a specificity of 91.8%. The area under the curve (AUC) of the final model was 0.91, indicating high predictive accuracy.

Conclusions: SWE is an independent predictor of recurrence risk in GD. When combined with traditional clinical indicators, it significantly enhances the predictive capability for GD recurrence. The risk score model provides a simple and effective tool for individualized management and optimization of treatment strategies.