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左旋甲状腺素治疗期间的 TSH 轨迹:巴西成人健康纵向研究(ELSA-Brasil)队列研究。

TSH Trajectories During Levothyroxine Treatment in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) Cohort.

机构信息

Section of Endocrinology, Diabetes, and Metabolism, University of Chicago, Chicago, IL 60637, USA.

Section of General Internal Medicine, University of Chicago, Chicago, IL 60637, USA.

出版信息

J Clin Endocrinol Metab. 2024 Nov 18;109(12):3065-3075. doi: 10.1210/clinem/dgae294.

Abstract

CONTEXT

Thyroid-stimulating hormone (TSH) trajectory classification represents a novel approach to defining the adequacy of levothyroxine (LT4) treatment for hypothyroidism over time.

OBJECTIVE

This is a proof of principle study that uses longitudinal clinical data, including thyroid hormone levels from a large prospective study to define classes of TSH trajectories and examine changes in cardiovascular (CV) health markers over the study period.

METHODS

Growth mixture modeling (GMM), including latent class growth analysis (LCGA), was used to classify LT4-treated individuals participating in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) based on serial TSH levels. Repeated measure analyses were then utilized to assess within-class changes in blood pressure, lipid levels, hemoglobin A1c, and CV-related medication utilization.

RESULTS

From the 621 LT4-treated study participants, the best-fit GMM approach identified 4 TSH trajectory classes, as defined by their relationship to the normal TSH range: (1) high-high normal TSH, (2) normal TSH, (3) normal to low TSH, and (4) low to normal TSH. Notably, the average baseline LT4 dose was lowest in the high-high normal TSH group (77.7 µg, P < .001). There were no significant differences in CV health markers between the classes at baseline. At least 1 significant difference in CV markers occurred in all classes, highlighted by the low to normal class, in which total and high-density lipoprotein cholesterol, triglycerides, and A1c all increased significantly (P = .049, P < .001, P < .001, and P = .001, respectively). Utilization of antihypertensive, antihyperlipidemic, and antidiabetes medications increased in all classes.

CONCLUSION

GMM/LCGA represents a viable approach to define and examine LT4 treatment by TSH trajectory. More comprehensive datasets should allow for more complex trajectory modeling and analysis of clinical outcome differences between trajectory classes.

摘要

背景

促甲状腺激素(TSH)轨迹分类代表了一种定义甲状腺功能减退症患者左甲状腺素(LT4)治疗随时间变化充分性的新方法。

目的

本研究使用包括来自大型前瞻性研究的甲状腺激素水平在内的纵向临床数据,通过定义 TSH 轨迹类别并检查研究期间心血管(CV)健康标志物的变化,来验证这一原理。

方法

采用增长混合物模型(GMM),包括潜在类别增长分析(LCGA),根据连续 TSH 水平对参与巴西成人健康纵向研究(ELSA-Brasil)的 LT4 治疗个体进行分类。然后利用重复测量分析评估血压、血脂水平、糖化血红蛋白(HbA1c)和与 CV 相关的药物使用在各分类内的变化。

结果

在 621 名接受 LT4 治疗的研究参与者中,最佳拟合 GMM 方法确定了 4 种 TSH 轨迹类别,这些类别与正常 TSH 范围有关:(1)高-高正常 TSH,(2)正常 TSH,(3)正常至低 TSH,和(4)低至正常 TSH。值得注意的是,高-高正常 TSH 组的平均基线 LT4 剂量最低(77.7μg,P<.001)。在基线时,各组间 CV 健康标志物无显著差异。在所有类别中均至少出现了 1 个 CV 标志物的显著差异,以低至正常类最为明显,其中总胆固醇和高密度脂蛋白胆固醇、甘油三酯和 A1c 均显著增加(P=0.049、P<.001、P<.001 和 P=0.001)。所有类别中降压、降脂和降糖药物的使用率均增加。

结论

GMM/LCGA 是一种可行的方法,可以通过 TSH 轨迹来定义和检查 LT4 治疗。更全面的数据集应允许对更复杂的轨迹模型进行分析,并分析轨迹类别之间的临床结局差异。

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