Serum neurofilament light chain correlations in patients with a first clinical demyelinating event in the REFLEX study: a <i>post hoc</i> analysis
Bibliographic record
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".