Original research A meta-analysis on the efficacy and tolerability of natalizumab in relapsing multiple sclerosis
Bibliographic record
Abstract
INTRODUCTION: Natalizumab is a new humanized monoclonal antibody used in multiple sclerosis (MS). The aim of this meta-analysis was to evaluate the efficacy and tolerability of this drug in relapsing MS. PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials were searched for studies that investigated the efficacy and/or tolerability of natalizumab in MS. Data were collected from 1966 to 2008 (up to October). MATERIAL AND METHODS: THE SEARCH TERMS WERE: "multiple sclerosis" or "MS" and "natalizumab". "Mean change in Expanded Disability Status Scale (EDSS)", "number of patients with at least one relapse", and "number of patients with at least one new gadolinium (Gd)-enhancing lesion" were the key outcomes of interest for assessment of efficacy. "Any adverse events", "serious adverse events", "death", and "withdrawal because of adverse events" were the key outcomes for tolerability. Among existing trials, four randomized placebo controlled clinical trials met our criteria and were included. RESULTS: Pooled relative risk for at least one relapse in four trials including all doses was 0.7, with a non-significant RR (95% CI: 0.42-1.17, p = 0. 17). Summary RR for at least one relapse in two trials in which doses of 3 mg/kg or 6 mg/kg or 300 mg every 4 weeks were administered gave a value of 0.5 asa significant RR (95% CI: 0.42-0.61, p < 0.0001). The summary RR for at least one new Gd-enhancing lesion was 0.22, a non-significant RR (95% CI: 0.05-1.01, p = 0.051). Three deaths were reported in the natalizumab group. Comparing adverse events between natalizumab and placebo yielded a non-significant RR of 0.99 (95% CI: 0.96-1.01, p = 0.34) for any adverse events (n = 3), and a significant RR of 0.39 (95% CI: 0.29-0.52, p < 0.0001) for serious adverse events (n = 2). The summary RR for withdrawal due to adverse events by natalizumab vs. placebo therapy between two trials was 1.43, a non-significant RR (95% CI: 0.68-3.02, p = 0.35). CONCLUSIONS: It seems that using 3 or 6 mg/kg every 4 weeks is the best method of administration of natalizumab for preventing relapse and occurrence of new Gd-enhancing lesions. The current data on the efficacy and safety of natalizumab are insufficient to reach a convincing conclusion and thus further clinical trials are still needed.
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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 | 0.026 | 0.056 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.070 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".