PDF(Pubmed)
Abstract：
A subset of Graves\' disease (GD) patients develops refractory hyperthyroidism, posing challenges in treatment decisions. The predictive value of baseline characteristics and early therapy indicators in identifying high risk individuals is an area worth exploration.
A prospective cohort study (2018-2022) involved 597 newly diagnosed adult GD patients undergoing methimazole (MMI) treatment. Baseline characteristics and 3-month therapy parameters were utilized to develop predictive models for refractory GD, considering antithyroid drug (ATD) dosage regimens.
Among 346 patients analyzed, 49.7% developed ATD-refractory GD, marked by recurrence and sustained Thyrotropin Receptor Antibody (TRAb) positivity. Key baseline factors, including younger age, Graves\' ophthalmopathy (GO), larger goiter size, and higher initial free triiodothyronine (fT3), free thyroxine (fT4), and TRAb levels, were all significantly associated with an increased risk of refractory GD, forming the baseline predictive model (Model A). Subsequent analysis based on MMI cumulative dosage at 3 months resulted in two subgroups: a high cumulative dosage group (average ≥ 20 mg/day) and a medium-low cumulative dosage group (average < 20 mg/day). Absolute values, percentage changes, and cumulative values of thyroid function and autoantibodies at 3 months were analyzed. Two combined predictive models, Model B (high cumulative dosage) and Model C (medium-low cumulative dosage), were developed based on stepwise regression and multivariate analysis, incorporating additional 3-month parameters beyond the baseline. In both groups, these combined models outperformed the baseline model in terms of discriminative ability (measured by AUC), concordance with actual outcomes (66.2% comprehensive improvement), and risk classification accuracy (especially for Class I and II patients with baseline predictive risk < 71%). The reliability of the above models was confirmed through additional analysis using random forests. This study also explored ATD dosage regimens, revealing differences in refractory outcomes between predicted risk groups. However, adjusting MMI dosage after early risk assessment did not conclusively improve the prognosis of refractory GD.
Integrating baseline and early therapy characteristics enhances the predictive capability for refractory GD outcomes. The study provides valuable insights into refining risk assessment and guiding personalized treatment decisions for GD patients.
A prospective cohort study (2018-2022) involved 597 newly diagnosed adult GD patients undergoing methimazole (MMI) treatment. Baseline characteristics and 3-month therapy parameters were utilized to develop predictive models for refractory GD, considering antithyroid drug (ATD) dosage regimens.
Among 346 patients analyzed, 49.7% developed ATD-refractory GD, marked by recurrence and sustained Thyrotropin Receptor Antibody (TRAb) positivity. Key baseline factors, including younger age, Graves\' ophthalmopathy (GO), larger goiter size, and higher initial free triiodothyronine (fT3), free thyroxine (fT4), and TRAb levels, were all significantly associated with an increased risk of refractory GD, forming the baseline predictive model (Model A). Subsequent analysis based on MMI cumulative dosage at 3 months resulted in two subgroups: a high cumulative dosage group (average ≥ 20 mg/day) and a medium-low cumulative dosage group (average < 20 mg/day). Absolute values, percentage changes, and cumulative values of thyroid function and autoantibodies at 3 months were analyzed. Two combined predictive models, Model B (high cumulative dosage) and Model C (medium-low cumulative dosage), were developed based on stepwise regression and multivariate analysis, incorporating additional 3-month parameters beyond the baseline. In both groups, these combined models outperformed the baseline model in terms of discriminative ability (measured by AUC), concordance with actual outcomes (66.2% comprehensive improvement), and risk classification accuracy (especially for Class I and II patients with baseline predictive risk < 71%). The reliability of the above models was confirmed through additional analysis using random forests. This study also explored ATD dosage regimens, revealing differences in refractory outcomes between predicted risk groups. However, adjusting MMI dosage after early risk assessment did not conclusively improve the prognosis of refractory GD.
Integrating baseline and early therapy characteristics enhances the predictive capability for refractory GD outcomes. The study provides valuable insights into refining risk assessment and guiding personalized treatment decisions for GD patients.
摘要：
背景：Graves病（GD）患者的一部分发展为难治性甲状腺功能亢进，在治疗决策中提出挑战。基线特征和早期治疗指标在识别高危个体中的预测价值是一个值得探索的领域。
方法：一项前瞻性队列研究（2018-2022年）涉及597例新诊断的成人GD患者接受甲他咪唑（MMI）治疗。基线特征和3个月治疗参数用于建立难治性GD的预测模型，考虑抗甲状腺药物（ATD）剂量方案。
结果：在分析的346例患者中，49.7%开发了ATD-耐火材料GD，以复发和持续的促甲状腺激素受体抗体（TRAb）阳性为标志。关键基线因素,包括年龄较小,格雷夫斯眼病（GO），较大的甲状腺肿大小，和较高的初始游离三碘甲状腺原氨酸（fT3），游离甲状腺素(fT4),和TRAb水平，都与难治性GD的风险增加显著相关，形成基线预测模型(模型A)。基于3个月时MMI累积剂量的后续分析导致两个亚组:高累积剂量组(平均≥20mg/天)和中低累积剂量组(平均<20mg/天)。绝对值,百分比变化，分析3个月时甲状腺功能和自身抗体的累积值。两个组合的预测模型，模型B（高累积剂量）和模型C（中低累积剂量），是基于逐步回归和多变量分析开发的，纳入超出基线的额外3个月参数。在这两组中,这些组合模型在辨别能力(由AUC衡量)方面优于基线模型，与实际结果一致(66.2%的综合改善)，和风险分类准确性（尤其是基线预测风险<71％的I类和II类患者）。通过使用随机森林的额外分析证实了上述模型的可靠性。本研究还探讨了ATD给药方案，揭示预测风险组之间难治性结局的差异。然而,早期风险评估后调整MMI剂量并不能最终改善难治性GD的预后.
结论：整合基线和早期治疗特征可增强难治性GD结局的预测能力。该研究为完善GD患者的风险评估和指导个性化治疗决策提供了有价值的见解。
方法：一项前瞻性队列研究（2018-2022年）涉及597例新诊断的成人GD患者接受甲他咪唑（MMI）治疗。基线特征和3个月治疗参数用于建立难治性GD的预测模型，考虑抗甲状腺药物（ATD）剂量方案。
结果：在分析的346例患者中，49.7%开发了ATD-耐火材料GD，以复发和持续的促甲状腺激素受体抗体（TRAb）阳性为标志。关键基线因素,包括年龄较小,格雷夫斯眼病（GO），较大的甲状腺肿大小，和较高的初始游离三碘甲状腺原氨酸（fT3），游离甲状腺素(fT4),和TRAb水平，都与难治性GD的风险增加显著相关，形成基线预测模型(模型A)。基于3个月时MMI累积剂量的后续分析导致两个亚组:高累积剂量组(平均≥20mg/天)和中低累积剂量组(平均<20mg/天)。绝对值,百分比变化，分析3个月时甲状腺功能和自身抗体的累积值。两个组合的预测模型，模型B（高累积剂量）和模型C（中低累积剂量），是基于逐步回归和多变量分析开发的，纳入超出基线的额外3个月参数。在这两组中,这些组合模型在辨别能力(由AUC衡量)方面优于基线模型，与实际结果一致(66.2%的综合改善)，和风险分类准确性（尤其是基线预测风险<71％的I类和II类患者）。通过使用随机森林的额外分析证实了上述模型的可靠性。本研究还探讨了ATD给药方案，揭示预测风险组之间难治性结局的差异。然而,早期风险评估后调整MMI剂量并不能最终改善难治性GD的预后.
结论：整合基线和早期治疗特征可增强难治性GD结局的预测能力。该研究为完善GD患者的风险评估和指导个性化治疗决策提供了有价值的见解。
