背景:血清抗甲状腺过氧化物酶抗体(anti-TPO)和抗甲状腺球蛋白抗体(anti-Tg)水平是诊断自身免疫性疾病的关键指标,尤其是自身免疫性甲状腺炎.在甲状腺自身抗体从阴性转为阳性之前,尚不清楚是否有任何临床指标在体内起到警示作用。
目的:建立甲状腺自身抗体阳性血清转换的早期预测模型。
方法:本回顾性队列研究收集了基于临床实验室数据的信息。使用逻辑回归模型分析与甲状腺自身抗体改变为异常状态相关的危险因素。采用机器学习方法建立预警模型,并使用列线图进行模型性能评估和可视化。接收器工作特性(ROC)曲线,校正曲线,和决策曲线分析用于内部和外部验证。
结果:Logistic回归分析显示,白蛋白与球蛋白的比值,甘油三酯水平,肝功能和一些代谢相关指标中的谷氨酸水平,代谢相关指标中的高密度脂蛋白C,肾功能指标和胱抑素C均为甲状腺抗体转换的危险因素(P<0.05)。此外,血液计数中的几项指标与甲状腺转换相关(P<0.05)。游离甲状腺素与游离三碘甲状腺原氨酸比例的变化是甲状腺抗体阳性转化的危险因素(ORfT4/fT3=1.763;95%置信区间1.554-2.000)。基于临床实验室指标正向影响的预警模型曲线下面积(AUC),年龄,性别为0.85,通过内部(AUC0.8515)和外部(AUC0.8378)验证。
结论:抗TPO和抗Tg转换预警模型结合常规体检中一些临床实验室指标具有稳定的预警效能。
BACKGROUND: Serum anti-thyroid peroxidase antibody (anti-TPO) and anti-thyroglobulin antibody (anti-Tg) levels are key indicators for the diagnosis of autoimmune diseases, especially autoimmune thyroiditis. Before the thyroid autoantibodies turn from negative to positive, it is unknown whether any clinical indicators in the body play a warning role.
OBJECTIVE: To establish an early prediction model of seroconversion to positive thyroid autoantibodies.
METHODS: This retrospective cohort study collected information based on clinical laboratory data. A logistic regression model was used to analyse the risk factors associated with a change in thyroid autoantibodies to an abnormal status. A machine-learning approach was employed to establish an early warning model, and a nomogram was used for model performance assessment and visualisation. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses were used for internal and external validation.
RESULTS: Logistic regression analysis revealed that albumin to globulin ratio, triglyceride levels, and Glutamic acid levels among liver function and some metabolism-related indicators, high density lipoprotein C among metabolism-related indicators, and cystatin C among renal function indicators were all risk factors for thyroid antibody conversion (P < 0.05). In addition, several indicators in the blood count correlated with thyroid conversion (P < 0.05). Changes in the ratio of free thyroxine to free triiodothyronine were a risk factor for positive thyroid antibody conversion (ORfT4/fT3 = 1.763; 95% confidence interval 1.554-2.000). The area under the curve (AUC) of the early warning model based on the positive impact of clinical laboratory indicators, age, and sex was 0.85, which was validated by both internal (AUC 0.8515) and external (AUC 0.8378) validation.
CONCLUSIONS: The early warning model of anti-TPO and anti-Tg conversion combined with some clinical laboratory indicators in routine physical examination has a stable warning efficiency.