Association of plasma neurofilament light chain with disease activity in chronic inflammatory demyelinating polyradiculoneuropathy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: This study was undertaken to explore associations between plasma neurofilament light chain (pNfL) concentration (pg/ml) and disease activity in patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) and examine the usefulness of pNfL concentrations in determining disease remission. METHODS: We examined pNfL concentrations in treatment-naïve CIDP patients (n = 10) before and after intravenous immunoglobulin (IVIg) induction treatment, in pNfL concentrations in patients on maintenance IVIg treatment who had stable (n = 15) versus unstable disease (n = 9), and in clinically stable IVIg-treated patients (n = 10) in whom we suspended IVIg to determine disease activity and ongoing need for maintenance IVIg. pNfL concentrations in an age-matched healthy control group were measured for comparison. RESULTS: Among treatment-naïve patients, pNfL concentration was higher in patients before IVIg treatment than healthy controls and subsequently reduced to be comparable to control group values after IVIg induction. Among CIDP patients on IVIg treatment, pNfL concentration was significantly higher in unstable patients than stable patients. A pNFL concentration > 16.6 pg/ml distinguished unstable treated CIDP from stable treated CIDP (sensitivity = 86.7%, specificity = 66.7%, area under receiver operating characteristic curve = 0.73). Among the treatment withdrawal group, there was a statistically significant correlation between pNfL concentration at time of IVIg withdrawal and the likelihood of relapse (r = 0.72, p < 0.05), suggesting an association of higher pNfL concentration with active disease. CONCLUSIONS: pNfL concentrations may be a sensitive, clinically useful biomarker in assessing subclinical disease activity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".