Department of Medical Endocrinology, Copenhagen University Hospital Rigshospitalet, Blegdamsvej, Denmark.
Eur J Endocrinol. 2019 Sep;181(3):R119-R131. doi: 10.1530/EJE-19-0234.
Prediction models are of a great assistance for predicting the development of a disease, detecting or screening undiagnosed patients, predicting the effectiveness of a treatment and helping toward better decision-making. Recently, three predictive scores in the field of autoimmune thyroid disease (AITD) have been introduced: The Thyroid Hormones Event Amsterdam (THEA) score: a predictive score of the development of overt AITD, the Graves' Events After Therapy (GREAT) score: a prediction score for the risk of recurrence after antithyroid drugs withdrawal and the Prediction Graves' Orbitopathy (PREDIGO) score: a prediction score for the development of Graves' orbitopathy in newly diagnosed patients with Graves' hyperthyroidism. Their construction, clinical applicability, the possible preventative measurements which can be taken to diminish the risks and the potential future developments which can improve the accuracy of the predictive scores are discussed in this review.
预测模型对于预测疾病的发展、检测或筛查未确诊的患者、预测治疗效果以及帮助做出更好的决策具有重要意义。最近,在自身免疫性甲状腺疾病(AITD)领域引入了三个预测评分:甲状腺激素事件阿姆斯特丹(THEA)评分:显性 AITD 发展的预测评分、格雷夫斯病治疗后事件(GREAT)评分:抗甲状腺药物停药后复发风险的预测评分以及预测格雷夫斯眼病(PREDIGO)评分:新诊断的格雷夫斯甲亢患者中格雷夫斯眼病的预测评分。本文综述了这些评分的构建、临床适用性、可能采取的降低风险的预防措施以及可能提高预测评分准确性的未来发展。