136 NOVA primary results randomised controlled study of natalizumab Q6W versus continued Q4W treatment for MS
Bibliographic record
Abstract
Background Natalizumab every-6-week (Q6W) dosing is associated with lower progressive multifocal leukoencephalopathy risk than every-4-week dosing (Q4W) in retrospective analyses. NOVA is the first randomised trial to assess Q6W efficacy. Objective Evaluate natalizumab Q6W efficacy in patients previously treated with natalizumab Q4W for ≥12 months compared with continuation of Q4W over 72 weeks. Methods NOVA is a randomised, controlled, open-label, rater-blinded phase 3b trial. Included patients were treated with natalizumab Q4W without relapse for ≥12 months. Patients were randomised 1:1 to Q4W (n=248) or Q6W (n=251). The primary endpoint was new/newly enlarging T2 (N/NET2) lesions. Secondary endpoints included clinical and safety outcomes. Results Proportions of patients with N/NET2 lesions were low in both arms (Q4W:4.1%; Q6W:4.3%). Differ- ences in mean N/NET2 lesions for Q4W and Q6W (primary estimand: 0.05 vs 0.20 [P=0.0755]; secondary estimand: 0.06 vs 0.31 [P=0.0437]) were driven by two Q6W patients with extreme (≥25) values. Secondary outcomes were similar for Q4W and Q6W. Conclusions Overall, NOVA data suggest most patients stable on natalizumab Q4W can switch to Q6W without clinically meaningful loss of efficacy. Support: Biogen. Disclosures on poster.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".