Endocrine Abstracts

Graves’ disease (GD) poses significant challenges in management, particularly due to its higher prevalence in women and the diverse treatment modalities available. Antithyroid drugs (ATD), radioactive iodine (RAI) therapy, and thyroidectomy each offer distinct advantages and risks. While ATD is initially favoured for its safety profile, it carries a notable relapse rate and considerable costs. In contrast, RAI boasts a lower relapse rate but elevates the risk of hypothyroidism and ophthalmopathy. Thyroidectomy, although effective, remains a tertiary option due to its invasiveness and associated risks. Current NICE guidelines recommend RAI as a primary treatment for GD, reflecting its efficacy and cost-effectiveness. However, concerns persist regarding its complications, primarily hypothyroidism and ophthalmopathy. This retrospective study, conducted over two decades at a tertiary centre in the United Kingdom, aims to identify predictive factors for relapse in GD patients, thereby optimising treatment selection. Among 1236 patients initially treated with ATD, only 350 eventually received RAI. Statistical analyses revealed that age, thyrotropin receptor antibody (TRAb) levels at diagnosis, and peak free thyroxine (fT4) levels were significantly associated with relapse. Notably, higher TRAb and fT4 levels correlated with increased relapse risk. These findings align with existing literature, emphasizing the importance of TRAb and fT4 in predicting relapse. While ATD remains preferable for its short-term benefits, the study underscores the need to identify high-risk patients early for prompt RAI initiation. Developing a predictive scoring system based on prospective studies could aid clinicians in personalised treatment decisions, minimising unnecessary ATD courses and subsequent relapses. Such an approach not only reduces patient morbidity but also offers a more cost-effective strategy for healthcare systems like the National Health Service (NHS). Future efforts should focus on refining risk stratification tools to optimise GD management and improve patient outcomes.