High serum neurofilament light chain normalizes after hematopoietic stem cell transplantation for MS
Bibliographic record
Abstract
Objective To evaluate neurofilament light chain (NfL) levels in serum and CSF of patients with aggressive MS pre- and post-treatment with immunoablation followed by autologous hematopoietic stem cell transplantation (IAHSCT) and examine associations with clinical and MRI outcomes. Methods Paired serum and CSF in addition to MRI and clinical measures were collected on 23 patients with MS at baseline and 1 and 3 years post-IAHSCT. An additional 33 sera and CSF pairs were taken from noninflammatory neurologic controls. NfL levels were quantitated using the Simoa platform (Quanterix). Results Baseline MS NfL levels were significantly elevated relative to controls in serum (p = 0.001) and CSF (p = 0.001). Following IAHSCT, high pretreatment NfL levels significantly reduced in serum (p = 0.0023) and CSF (p = 0.0068) and were not significantly different from controls. Serum and CSF NfL levels highly correlated (r = 0.81, p < 0.0001). Baseline NfL levels were associated with worse pretreatment disease measures (Expanded Disability Status Scale [EDSS], relapses, MRI lesions, and MR spectroscopy (MRS) N-acetylaspartate/creatine). Elevated baseline NfL levels were associated with persistently worse indices of disease burden post-IAHSCT (sustained EDSS progression, cognition, quality of life, T1 and T2 lesion volumes, MRS, and brain atrophy). Conclusion These data substantiate that serum and CSF NfL levels reflect disease severity and treatment response in patients with MS and may therefore be a useful biomarker. Baseline serum levels associated with markers of pretreatment disease severity and post-treatment outcomes. Classification of evidence This study provides Class II evidence that for patients with aggressive MS, serum NfL levels are associated with disease severity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".