Serum neurofilament light chain correlations in patients with a first clinical demyelinating event in the REFLEX study: a post hoc analysis.

IF 5.4 3区材料科学 Q2 CHEMISTRY, PHYSICAL

ACS Applied Energy Materials Pub Date : 2024-03-29 eCollection Date: 2024-01-01 DOI:10.1177/17562864241239101

Jens Kuhle, David Leppert, Giancarlo Comi, Nicola de Stefano, Ludwig Kappos, Mark S Freedman, Andrea Seitzinger, Sanjeev Roy

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引用次数: 0

Abstract

Background: In REFLEX, subcutaneous interferon beta-1a (sc IFN β-1a) delayed the onset of multiple sclerosis (MS) in patients with a first clinical demyelinating event (FCDE).

Objectives: This post hoc analysis aimed to determine whether baseline serum neurofilament light (sNfL) chain can predict conversion to MS and whether correlations exist between baseline sNfL and magnetic resonance imaging (MRI) metrics.

Methods: sNfL was measured for 494 patients who received sc IFN β-1a 44 μg once weekly (qw; n = 168), three times weekly (tiw; n = 161), or placebo (n = 165) over 24 months. Median baseline sNfL (26.1 pg/mL) was used to define high/low sNfL subgroups. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox's proportional hazard model to determine factors influencing the risk of conversion to MS. Kaplan-Meier estimates calculated median time-to-conversion to MS (McDonald 2005 criteria) or clinically definite MS (CDMS; Poser criteria). Correlations between sNfL and MRI findings were assessed using Spearman's rank correlation coefficient (r).

Results: Multivariable models indicated that high baseline sNfL was associated with the likelihood of converting to MS and inversely to time-to-conversion (HR = 1.3, 95% CI: 1.03-1.64; p = 0.024). Significant additional factors affecting conversion to McDonald MS were on-study treatment (sc IFN β-1a/placebo; qw: HR = 0.59, 95% CI: 0.46-0.76; tiw: HR = 0.45, 95% CI: 0.34-0.59), classification of FCDE (monofocal/multifocal; HR = 0.69, 95% CI: 0.55-0.85), and most baseline imaging findings (T2 and T1 gadolinium-enhancing [Gd+] lesions; HR = 1.02, 95% CI: 1.01-1.03 and HR = 1.07, 95% CI: 1.03-1.11); all p ⩽ 0.001. Conversion to CDMS showed similar results. At month 24, sNfL was strongly correlated with a mean number of combined unique active (r = 0.71), new T2 (r = 0.72), and new T1 Gd+ (r = 0.60) lesions; weak correlations were observed between sNfL and clinical outcomes for all treatment groups.

Conclusion: Higher baseline sNfL was associated with an increased risk of MS conversion, a risk that was mitigated by treatment with sc IFN β-1a tiw.

Trial registration: ClinicalTrials.gov identifier: NCT00404352. Date registered: 28 November 2006.

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REFLEX研究中首次临床脱髓鞘事件患者血清神经丝蛋白轻链的相关性：事后分析。

研究背景在REFLEX研究中，皮下注射干扰素β-1a（sc IFN β-1a）可延迟首次临床脱髓鞘事件（FCDE）患者多发性硬化症（MS）的发病：方法：在 24 个月内接受 sc IFN β-1a 44 μg 每周一次（qw；n = 168）、每周三次（tiw；n = 161）或安慰剂（n = 165）治疗的 494 名患者的 sNfL 均进行了测量。基线 sNfL 中位数（26.1 pg/mL）用于定义高/低 sNfL 亚组。使用 Cox 比例危险模型计算危险比 (HR) 和 95% 置信区间 (CI)，以确定影响转为 MS 风险的因素。Kaplan-Meier估计值计算了转为多发性硬化症（McDonald 2005标准）或临床确诊多发性硬化症（CDMS；Poser标准）的中位时间。使用斯皮尔曼等级相关系数（r）评估了 sNfL 与 MRI 结果之间的相关性：多变量模型显示，高基线 sNfL 与转为 MS 的可能性相关，与转为 MS 的时间成反比（HR = 1.3，95% CI：1.03-1.64；P = 0.024）。影响转为麦克唐纳多发性硬化症的其他重要因素是研究中的治疗（sc IFN β-1a/安慰剂；qw：HR=0.59，95% CI：0.46-0.76；tiw：HR=0.45，95% CI：0.34-0.59）、FCDE分类（单灶/多灶；HR=0.69，95% CI：0.55-0.85）和大多数基线成像结果（T2和T1钆增强[Gd+]病灶；HR=1.02，95% CI：1.01-1.03和HR=1.07，95% CI：1.03-1.11）；所有P均⩽ 0.001。转为 CDMS 的结果类似。第24个月时，sNfL与合并的唯一活跃病灶（r = 0.71）、新T2病灶（r = 0.72）和新T1 Gd+病灶（r = 0.60）的平均数量密切相关；在所有治疗组中，sNfL与临床结果之间的相关性较弱：结论：较高的基线sNfL与MS转归风险的增加有关，而sc IFN β-1a tiw治疗可减轻这一风险：试验注册：ClinicalTrials.gov identifier：NCT00404352。注册日期：2006 年 11 月 28 日。

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来源期刊

ACS Applied Energy Materials Materials Science-Materials Chemistry

CiteScore

10.30

自引率

6.20%

发文量

1368

期刊介绍： ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.