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Tristan Struja, Marina Kaeslin, Fabienne Boesiger, Rebecca Jutzi, Noemi Imahorn, Alexander Kutz, Luca Bernasconi, Esther Mundwiler, Beat Mueller, Mirjam Christ-Crain, Fabian Meienberg, Fahim Ebrahimi, Christoph Henzen, Stefan Fischli, Marius Kraenzlin, Christian Meier, Philipp Schuetz, External validation of the GREAT score to predict relapse risk in Graves' disease: results from a multicenter, retrospective study with 741 patients, European Journal of Endocrinology, Volume 176, Issue 4, Apr 2017, Pages 413–419, https://doi.org/10.1530/EJE-16-0986
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Abstract
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.
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.
We retrospectively analyzed data (2004–2014) of patients with a first episode of Graves' hyperthyroidism from four Swiss endocrine outpatient clinics.
Relapse of hyperthyroidism analyzed by multivariate Cox regression.
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 T4, 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).
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.