主管单位:中华人民共和国
国家卫生健康委员会
主办单位:中国医师协会
总编辑:杨秋
编辑部主任:吴翔宇
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英文作者:Zhao Tian Chen Tong Zheng Yu Zhao Na Zhang Jietao
英文单位:Department of General Medicine the Affiliated Hospital of Qingdao University Qingdao 266000 China
关键词:毒性弥漫性甲状腺肿;促甲状腺激素受体自身抗体;危险因素;预测模型
英文关键词:Toxicdiffusegoiter;Thyrotropinreceptorautoantibody;Riskfactors;Predictivemodel
目的 探讨应用抗甲状腺药物(ATD)治疗的毒性弥漫性甲状腺肿(Graves病)患者预后的影响因素,并建立Graves病预后相关预测模型。方法 回顾性选取2012年10月至2019年10月于青岛大学附属医院门诊初诊为Graves病的患者191例,根据治疗周期及复发情况将患者分为缓解组(109例)和未缓解组(82例)。比较2组患者年龄、性别、家族史、甲状腺肿大程度及相关实验室指标。采用单因素Logistic回归模型分析影响ATD治疗Graves病患者预后的影响因素,通过多因素Logistic回归分析构建Graves病患者预后的预测模型,使用受试者工作特征(ROC)曲线对预测模型效能进行评价。结果 未缓解组年龄小于缓解组[(35.6±1.4)岁比(40.2±1.3)岁],初诊时、治疗6个月时促甲状腺激素受体自身抗体(TRAb)水平均高于缓解组[10.73(6.59,21.29)IU/L比8.85(4.59,16.92)IU/L、6.98(2.56,12.86)IU/L比2.45(1.05,5.01)IU/L],TRAb下降率低于缓解组[0.45(0.20,0.69)比0.65(0.49,0.84)],差异均有统计学意义(均P<0.05)。单因素Logistic回归分析结果显示年龄、初诊时TRAb、治疗6个月时TRAb、TRAb下降率为影响ATD治疗Graves病患者预后的危险因素(均P<0.05)。多因素Logistic回归分析结果显示年龄、初诊时TRAb、TRAb下降率为ATD治疗Graves病患者预后不良的独立危险因素(均P<0.05)。以年龄、初诊时TRAb、TRAb下降率构建Graves病患者预测模型,ROC曲线分析结果显示,预测模型用于预测ATD治疗Graves病患者预后的曲线下面积(AUC)为0.749(95%置信区间:0.681~0.808),截断值为0.42,约登指数为0.411,敏感度为0.659,特异度为0.752。预测模型的AUC及敏感度均高于各指标单独检测。结论 年龄、初诊时TRAb、TRAb下降率是影响ATD治疗Graves病患者不良预后的独立危险因素,由年龄、初诊时TRAb、TRAb下降率构建的预测模型对患者预后有较好的预测价值。
Objective To explore the prognostic influencing factors in patients with toxic diffuse goiter (Graves′ disease) treated with antithyroid drugs (ATD), and to construct the predictive model of the prognosis. Methods From October 2012 to October 2019, 191 outpatients of first-visit Graves′ disease were enrolled retrospectively from the Affiliated Hospital of Qingdao University. According to the theraputic cycle and relapse, they were divided into relieve group (109 cases) and non-relieve group (82 cases). The age, gender, family history, degree of goiter and relevant laboratory indicators were compared between the two groups. Univariate Logistic regression model was used to analyze prognostic influencing factors for Graves′ disease patients treated with ATD. The predictive model for the prognosis was constructed by multivariate Logistic analysis, and its efficacy was evaluated by receiver operating characteristic (ROC) curve. Results Compared to relieve group, the age of non-relieve group was lower[(35.6±1.4)years vs (40.2±1.3)years], levels of thyrotropin receptor autoantibody (TRAb) at first-visit and 6 months of treatment were higher[10.73(6.59,21.29)IU/L vs 8.85(4.59,16.92)IU/L, 6.98(2.56,12.86)IU/L vs 2.45(1.05,5.01)IU/L], and the falling rate of TRAb was lower[0.45(0.20,0.69) vs 0.65(0.49,0.84)](all P<0.05). Univariate Logistic regression analysis showed that age, TRAb at first-visit and 6 months of treatment, and falling rate of TRAb were prognostic risk factors for Graves′ disease patients treated with ATD (all P<0.05). Multivariate Logistic regression analysis showed that age, TRAb at first-visit and falling rate of TRAb were independent prognostic risk factors (all P<0.05). The predictive model was constructed with above three indicators. ROC curve analysis showed that the area under the curve (AUC) for the predictive model was 0.749 (95% confidence interval: 0.681-0.808), the cut-off value was 0.42, Youden index was 0.411, sensitivity was 0.659, and specificity was 0.752. The AUC and sensitivity of the predictive model were higher than each indicator individually. Conclusions The independent risk factors for poor prognosis of Graves′ disease patients treated with ATD are age, TRAb at first-visit and falling rate of TRAb. The predictive model constructed with above three indicators shows high predictive value in patient′s prognosis.
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