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多发性硬化症表型转变的模式与预测因素。

Patterns and predictors of multiple sclerosis phenotype transition.

作者信息

Pontieri Luigi, Greene Nupur, Wandall-Holm Malthe Faurschou, Geertsen Svend Sparre, Asgari Nasrin, Jensen Henrik Boye, Illes Zsolt, Schäfer Jakob, Jensen Rikke Marie, Sejbæk Tobias, Weglewski Arkadiusz, Mahler Mie Reith, Poulsen Mai Bang, Prakash Sivagini, Stilund Morten, Kant Matthias, Rasmussen Peter Vestergaard, Svendsen Kristina Bacher, Sellebjerg Finn, Magyari Melinda

机构信息

The Danish Multiple Sclerosis Registry, Department of Neurology, Copenhagen University Hospital-Rigshospitalet Glostrup, 2600 Glostrup, Denmark.

Sanofi, Cambridge, MA 02141, USA.

出版信息

Brain Commun. 2024 Nov 23;6(6):fcae422. doi: 10.1093/braincomms/fcae422. eCollection 2024.

Abstract

Currently, there are limited therapeutic options for patients with non-active secondary progressive multiple sclerosis. Therefore, real-world studies have investigated differences between patients with relapsing-remitting multiple sclerosis, non-active secondary progressive multiple sclerosis and active secondary progressive multiple sclerosis. Here, we explore patterns and predictors of transitioning between these phenotypes. We performed a cohort study using data from The Danish Multiple Sclerosis Registry. We included patients with a relapsing-remitting phenotype, registered changes to secondary progressive multiple sclerosis and subsequent transitions between relapsing and non-relapsing secondary progressive multiple sclerosis, which was defined by the presence of relapses in the previous 2 years. We analysed predictors of transitioning from relapsing-remitting multiple sclerosis to relapsing and non-relapsing secondary progressive multiple sclerosis, as well as between the secondary progressive states using a multi-state Markov model. We included 4413 patients with relapsing-remitting multiple sclerosis. Within a median follow-up of 16.2 years, 962 were diagnosed with secondary progressive multiple sclerosis by their treating physician. Of these, we classified 729 as non-relapsing and 233 as relapsing secondary progressive multiple sclerosis. The risk of transitioning from relapsing-remitting to non-relapsing secondary progressive multiple sclerosis included older age (hazard ratio per increase of 1 year in age: 1.044, 95% confidence interval: 1.035-1.053), male sex (hazard ratio for female: 0.735, 95% confidence interval: 0.619-0.874), fewer relapses (hazard ratio per each additional relapse: 0.863, 95% confidence interval: 0.823-0.906), higher expanded disability status scale (hazard ratio per each additional point: 1.522, 95% confidence interval: 1.458-1.590) and longer time on disease-modifying therapies (hazard ratio per increase of 1 year in treatment, high-efficacy disease-modifying therapy: 1.095, 95% confidence interval: 1.051-1.141; hazard ratio, moderate-efficacy disease-modifying therapy: 1.073, 95% confidence interval: 1.051-1.095). We did not find significant predictors associated with the transition from relapsing secondary progressive multiple sclerosis to non-relapsing secondary progressive multiple sclerosis, whereas older age (hazard ratio per increase of 1 year in age: 0.956, 95% confidence interval: 0.942-0.971) prevented the transition from non-relapsing secondary progressive multiple sclerosis to relapsing secondary progressive multiple sclerosis. Our study suggests that transitioning from relapsing-remitting multiple sclerosis to non-relapsing secondary progressive multiple sclerosis depends on well-known factors affecting diagnosing secondary progressive multiple sclerosis. Further transitions between non-relapsing and relapsing secondary progressive multiple sclerosis are only affected by age. These findings add to the knowledge of non-active secondary progressive multiple sclerosis, a patient group with unmet needs in terms of therapies.

摘要

目前,对于非活动性继发进展型多发性硬化症患者而言,治疗选择有限。因此,真实世界研究调查了复发缓解型多发性硬化症患者、非活动性继发进展型多发性硬化症患者和活动性继发进展型多发性硬化症患者之间的差异。在此,我们探讨这些表型之间转变的模式和预测因素。我们使用丹麦多发性硬化症登记处的数据进行了一项队列研究。我们纳入了复发缓解型表型的患者,记录了向继发进展型多发性硬化症的转变以及随后复发型和非复发型继发进展型多发性硬化症之间的转变,后者由过去2年中是否存在复发来定义。我们使用多状态马尔可夫模型分析了从复发缓解型多发性硬化症转变为复发型和非复发型继发进展型多发性硬化症的预测因素,以及继发进展状态之间的预测因素。我们纳入了4413例复发缓解型多发性硬化症患者。在中位随访16.2年期间,962例患者被其治疗医生诊断为继发进展型多发性硬化症。其中,我们将729例分类为非复发型,233例分类为复发型继发进展型多发性硬化症。从复发缓解型转变为非复发型继发进展型多发性硬化症的风险因素包括年龄较大(年龄每增加1岁的风险比:1.044,95%置信区间:1.035 - 1.053)、男性(女性的风险比:0.735,95%置信区间:0.619 - 0.874)、复发次数较少(每增加一次复发的风险比:0.863,95%置信区间:0.823 - 0.906)、扩展残疾状态量表评分较高(每增加一分的风险比:1.522,95%置信区间:1.458 - 1.590)以及疾病修饰治疗时间较长(治疗时间每增加1年,高效能疾病修饰治疗的风险比:1.095,95%置信区间:1.051 - 1.141;风险比,中效能疾病修饰治疗:1.073,95%置信区间:1.051 - 1.095)。我们未发现与从复发型继发进展型多发性硬化症转变为非复发型继发进展型多发性硬化症相关的显著预测因素,而年龄较大(年龄每增加1岁的风险比:0.956,95%置信区间:0.942 - 0.971)可防止从非复发型继发进展型多发性硬化症转变为复发型继发进展型多发性硬化症。我们的研究表明,从复发缓解型多发性硬化症转变为非复发型继发进展型多发性硬化症取决于影响继发进展型多发性硬化症诊断的已知因素。非复发型和复发型继发进展型多发性硬化症之间的进一步转变仅受年龄影响。这些发现增加了对非活动性继发进展型多发性硬化症的认识,这是一个在治疗方面有未满足需求的患者群体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/752c/11660925/76c585829f03/fcae422f2.jpg

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