4.6 Article

External validation of the GREAT score to predict relapse risk in Graves' disease: results from a multicenter, retrospective study with 741 patients

Journal

EUROPEAN JOURNAL OF ENDOCRINOLOGY
Volume 176, Issue 4, Pages 413-419

Publisher

BIOSCIENTIFICA LTD
DOI: 10.1530/EJE-16-0986

Keywords

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Funding

  1. Swiss National Science Foundation (SNSF Professorship) [PP00P3_150531/1]
  2. Research Council of the Kantonsspital Aarau [1410.000.044]

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Context: First-line treatment in Graves disease is often done with antithyroid agents (ATD), but relapse rates remain high making definite treatment necessary. Predictors for relapse risk help guiding initial treatment decisions. Objective: We aimed to externally validate the prognostic accuracy of the recently proposed Graves Recurrent Events After Therapy (GREAT) score to predict relapse risk in Graves disease. Design, setting and participants: We retrospectively analyzed data (2004-2014) of patients with a first episode of Graves' hyperthyroidism from four Swiss endocrine outpatient clinics. Main outcome measures: Relapse of hyperthyroidism analyzed by multivariate Cox regression. Results: Of the 741 included patients, 371 experienced a relapse (50.1%) after a mean follow-up of 25.6 months after ATD start. In univariate regression analysis, higher serum free T-4, higher thyrotropin-binding inhibitor immunoglobulin (TBII), younger age and larger goiter were associated with higher relapse risk. We found a strong increase in relapse risk with more points in the GREAT score from 33.8% in patients with GREAT class I (0-1 points), 59.4% in class II (2-3 points) with a hazard ratio of 1.79 (95% CI: 1.42-2.27, P < 0.001) and 73.6% in class III (4-6 points) with a hazard ratio of 2.24 (95% CI: 1.64-3.06, P < 0.001). Conclusions: Based on this retrospective analysis within a large patient population from a multicenter study, the GREAT score shows good external validity and can be used for assessing the risk for relapse in Graves disease, which influence the initial treatment decisions.

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