Safety, efficacy, and tolerability of alemtuzumab in pediatric patients with active relapsing-remitting multiple sclerosis: The LemKids study
Bibliographic record
Abstract
BACKGROUND: Limited licensed medications are available for multiple sclerosis (MS) in pediatric patients. OBJECTIVE: To evaluate the efficacy, safety, and tolerability of alemtuzumab in pediatric patients with relapsing-remitting multiple sclerosis (RRMS) and disease activity on prior disease-modifying therapies (DMTs). METHODS: LemKids was a multicenter, multinational, single-arm, open-label, switch (from ongoing DMT to alemtuzumab treatment) study in pediatric RRMS patients (aged 10-<18 years), with disease activity on DMT. The primary endpoint was a comparison of the number of new/enlarging T2 lesions on the magnetic resonance imaging of the brain between the prior-DMT period and alemtuzumab treatment. RESULTS: This study was prematurely terminated due to low enrollment and an European Medicines Agency Article-20 pharmacovigilance review of alemtuzumab in adult RRMS. Of 46 screened patients, 16 were enrolled; 12 completed prior-DMT treatment period; 11 received alemtuzumab of whom 7 completed treatment. Patients on alemtuzumab developed fewer new/enlarging T2 lesions compared with prior-DMT (7 vs 178, relative risk (95% confidence interval): 0.04 (0.01-0.14)). No significant pharmacodynamic changes or safety concerns were noted in this limited dataset. CONCLUSION: Alemtuzumab treatment was associated with a low number of new/enlarging T2 lesions in pediatric patients with RRMS and was safe and well tolerated in seven patients during infusion and the initial 4 months.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".