A Predictive Model for Graves' Disease Recurrence After Antithyroid Drug Therapy: A Retrospective Multicenter Cohort...

Area of Science:

• Endocrinology
• Clinical Medicine
• Pharmacology

Background:

• Graves' disease (GD) is a common autoimmune disorder leading to hyperthyroidism.
• Antithyroid drugs (ATDs) are a primary treatment, but recurrence after cessation is frequent.
• Predicting recurrence is essential for personalized treatment strategies.

Purpose of the Study:

• To identify factors predicting recurrence of Graves' disease after antithyroid drug cessation.
• To develop a predictive model for GD recurrence risk within the first year post-treatment using routine clinical parameters.

Main Methods:

• Observational cohort study using electronic health records from 3 U.S. academic centers.
• Analysis of demographic and clinical characteristics of patients with GD treated with ATDs.
• Development and validation of a predictive model and nomogram for GD recurrence.

Main Results:

• A total of 523 patients were included; 211 discontinued ATDs, with 142 used for model development.
• Recurrence within one year was observed in 37.44% of patients who discontinued ATDs.
• Increased age (per decade) and higher baseline free thyroxine (FT4) levels were significant predictors of recurrence.

Conclusions:

• A practical model using baseline age and FT4 levels can predict Graves' disease recurrence risk after ATD cessation.
• This model aids in initial therapeutic decision-making for patients with GD.
• Further research is needed to refine predictive models and identify additional recurrence factors.