Effect of dimethyl fumarate on lymphocytes in RRMS
Bibliographic record
Abstract
OBJECTIVE: To assess functional changes in lymphocyte repertoire and subsequent clinical implications during delayed-release dimethyl fumarate (DMF) treatment in patients with multiple sclerosis. METHODS: Using peripheral blood from several clinical trials of DMF, immune cell subsets were quantified using flow cytometry. For some patients, lymphocyte counts were assessed after DMF discontinuation. Incidence of adverse events, including serious and opportunistic infections, was assessed. RESULTS: In DMF-treated patients, absolute lymphocyte counts (ALCs) demonstrated a pattern of decline followed by stabilization, which also was reflected in the global reduction in numbers of circulating functional lymphocyte subsets. The relative frequencies of circulating memory T- and B-cell populations declined and naive cells increased. No increased incidence of serious infection or malignancy was observed for patients treated with DMF, even when stratified by ALC or T-cell subset frequencies. For patients who discontinued DMF due to lymphopenia, ALCs increased after DMF discontinuation; recovery time varied by ALC level at discontinuation. T-cell subsets closely correlated with ALCs in both longitudinal and cross-sectional analyses. CONCLUSIONS: T-cell counts, indicating that lymphocyte subset monitoring is not required for safety vigilance. No increased risk of serious infection was observed in patients with low T-cell subset counts. Monitoring ALC remains the most effective way of identifying patients at risk of subsequently developing prolonged moderate to severe lymphopenia, a risk factor for progressive multifocal leukoencephalopathy in DMF-treated patients. TRIAL REGISTRATION NUMBERS: EUDRA CT 2015-001973-42, NCT00168701, NCT00420212, NCT00451451, and NCT00835770.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".