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乙酰胆碱受体抗体阳性全身型重症肌无力各亚型中艾加莫德治疗反应的模式及预测因素

Patterns and predictors of therapeutic response to efgartigimod in acetylcholine receptor-antibody generalized myasthenia gravis subtypes.

作者信息

Jin Lei, Zou Zhangyu, Wang Qinzhou, Zeng Wenshuang, Jiang Qilong, Chen Jing, Shi Jianquan, Yu Yanyan, Hong Daojun, Zeng Quantao, Tan Song, Yue Yaoxian, Zhang Zhouao, Zhang Yong, Guo Xiuming, Du Lei, Zhao Zhongyan, Huang Shixiong, Chen Ying, Wu Zongtai, Yan Chong, Xi Jianying, Song Jie, Luo Sushan, Zhao Chongbo

机构信息

Huashan Rare Disease Center and Department of Neurology, Huashan Hospital, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China.

Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China.

出版信息

Ther Adv Neurol Disord. 2025 Feb 18;18:17562864251319656. doi: 10.1177/17562864251319656. eCollection 2025.

DOI:10.1177/17562864251319656
PMID:39974170
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11837134/
Abstract

BACKGROUND

Efgartigimod is an approved biologic for generalized myasthenia gravis (gMG), which is an autoimmune disease and can potentially be life-threatening. However, the therapeutic response to efgartigimod among the acetylcholine receptor gMG (AChR-gMG) subtypes remains inconclusive.

OBJECTIVE

To explore the patterns and predictors for the therapeutic response to efgartigimod among AChR-gMG subtypes.

DESIGN

This prospective, observational study included AChR-gMG patients treated with efgartigimod at 15 centers in China with a follow-up for at least 20 weeks.

METHODS

The primary outcome was the proportion of minimal symptom expression (MSE) responders, denoted by a Myasthenia Gravis Activities of Daily Living (MG-ADL) score of 0 or 1 within 4 weeks and maintained for ⩾4 weeks. AChR antibody-positive MG (AChR-MG) subtypes were classified into early onset myasthenia gravis (EOMG), late-onset myasthenia gravis (LOMG), and thymoma-associated myasthenia gravis (TAMG). The predictive factors for MSE responders were identified by univariate and multivariate logistic regression analysis.

RESULTS

One hundred sixteen patients were included with a median follow-up duration of 238 days (172.5-306.3). There were 50 (43.1%) patients with EOMG, 28 (24.1%) with LOMG and 38 (32.8%) with TAMG. After efgartigimod initiation, 35 (30.2%) patients were MSE responders, and the proportion of MSE responders was highest in the LOMG group (42.9%). The MG-ADL score reduction in the LOMG group was more significant than in the EOMG group by weeks 16 and 20 (both  = 0.022). Response patterns to efgartigimod among the AChR-MG subtypes differed as measured by the proportion of improved patients and MSE. LOMG presented sustained symptom control, while EOMG and TAMG showed more fluctuations. Eight TAMG patients (21.1%) switched to another biologic ( = 0.005). Baseline MG-ADL was an independent predictor for therapeutic response to efgartigimod ( < 0.001).

CONCLUSION

Our findings revealed patterns of treatment responses among AChR-gMG subtypes, with LOMG patients potentially presenting a more sustained response. These findings likely provide preliminary data for precision therapy in MG in the era of biologics.

TRIAL REGISTRATION

NCT04535843.

摘要

背景

艾加莫德是一种已获批用于治疗全身型重症肌无力(gMG)的生物制剂,gMG是一种自身免疫性疾病,可能会危及生命。然而,乙酰胆碱受体gMG(AChR - gMG)亚型对艾加莫德的治疗反应仍不明确。

目的

探讨AChR - gMG亚型对艾加莫德治疗反应的模式及预测因素。

设计

这项前瞻性观察性研究纳入了在中国15个中心接受艾加莫德治疗的AChR - gMG患者,随访至少20周。

方法

主要结局是最小症状表现(MSE)缓解者的比例,定义为在4周内重症肌无力日常生活活动(MG - ADL)评分为0或1,并维持至少4周。AChR抗体阳性MG(AChR - MG)亚型分为早发型重症肌无力(EOMG)、晚发型重症肌无力(LOMG)和胸腺瘤相关性重症肌无力(TAMG)。通过单因素和多因素逻辑回归分析确定MSE缓解者的预测因素。

结果

共纳入116例患者,中位随访时间为238天(172.5 - 306.3)。其中EOMG患者50例(43.1%),LOMG患者28例(24.1%),TAMG患者38例(32.8%)。开始使用艾加莫德后,35例(30.2%)患者为MSE缓解者,LOMG组MSE缓解者比例最高(42.9%)。在第16周和第20周时,LOMG组的MG - ADL评分下降比EOMG组更显著(均P = 0.022)。根据病情改善患者比例和MSE衡量,AChR - MG亚型对艾加莫德的反应模式不同。LOMG呈现持续的症状控制,而EOMG和TAMG则表现出更多波动。8例TAMG患者(21.1%)改用另一种生物制剂(P = 0.005)。基线MG - ADL是艾加莫德治疗反应的独立预测因素(P < 0.001)。

结论

我们的研究结果揭示了AChR - gMG亚型的治疗反应模式,其中LOMG患者可能呈现更持续的反应。这些发现可能为生物制剂时代MG的精准治疗提供初步数据。

试验注册

NCT04535843。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d5/11837134/2d039649b7e4/10.1177_17562864251319656-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d5/11837134/1fca3e2c462d/10.1177_17562864251319656-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d5/11837134/886f99e1c707/10.1177_17562864251319656-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d5/11837134/2d039649b7e4/10.1177_17562864251319656-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d5/11837134/1fca3e2c462d/10.1177_17562864251319656-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d5/11837134/886f99e1c707/10.1177_17562864251319656-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d5/11837134/2d039649b7e4/10.1177_17562864251319656-fig3.jpg

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