Advances in research on anti-thyroid drugs for recurrence risk factors and predictive models of Graves′ disease

Abstract

Graves′ disease, also known as diffuse toxic goiter, is an autoimmune disease with increased secretion of thyroid hormone. There are three effective treatments for Graves′ disease, which including anti-thyroid drugs (ATD), radioactive iodine and thyroidectomy. In general, ATD is the first choice of Graves′ disease treatment for domestic physicians, but the high recurrence rate has always been the deficiency of ATD treatment. Recurrence is mainly related to gender, age, smoking, course of disease, goiter and other factors. Among them, the reliability and applicability of single risk factor in evaluating the recurrence rate of Graves′ disease after ATD treatment are poor. The prediction model of multi-factor comprehensive score is helpful for the naive patients to choose the best treatment plan, to achieve the goal of precise treatment and to improve the remission rate of Graves′ disease drug treatment. In this paper, the reliability of risk factors for Graves′ disease recurrence after ATD treatment is evaluated, and the development and application of prediction models such as Graves′ recurrent events after therapy (GREAT) score, GREAT + score, and clinical severity score (CSS) are reviewed. Key words: Anti-thyroid drugs; Recurrence of Graves′ disease; Risk factor; Predictive model