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.