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Record W4290830430 · doi:10.1136/jnnp-2022-abn2.180

136 NOVA primary results randomised controlled study of natalizumab Q6W versus continued Q4W treatment for MS

2022· article· en· W4290830430 on OpenAlexaff
John Foley, Gilles Defer, Lana Zhovtis Ryerson, Jeffrey Cohen, Douglas L. Arnold, Helmut Butzkueven, Gary Cutter, Gavin Giovannoni, Joep Killestein

Bibliographic record

VenueJournal of Neurology Neurosurgery & Psychiatry · 2022
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsMcGill UniversityNeuroRx Research (Canada)
Fundersnot available
KeywordsNatalizumabMedicineClinical endpointDosingInternal medicinePediatricsRandomized controlled trialDisease

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.304
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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