Attack adjudication in neuromyelitis optica spectrum disorder: Substantiation of criteria by magnetic resonance imaging and biomarkers in N-MOmentum
Bibliographic record
Abstract
Background:The N-MOmentum trial investigated safety and efficacy of inebilizumab in participants with neuromyelitis optica spectrum disorder (NMOSD).Objective:Evaluate the attack identification process and adjudication committee (AC) performance in N-MOmentum.Methods:Adults (n = 230) with NMOSD and Expanded Disability Status Scale score ⩽8 were randomized (3:1) to inebilizumab 300 mg or placebo. The randomized controlled period was 28 weeks or until adjudicated attack. Attacks were adjudicated according to 18 predefined criteria. Magnetic resonance imaging (MRI) and biomarker (serum glial fibrillary acidic protein [sGFAP]) analyses were performed.Results:A total of 64 participant-reported neurological events occurred; 51 (80%) were investigator-determined to be attacks. The AC confirmed 43 of the investigator-determined attacks (84%). There was high inter- and intra-AC-member agreement. In 25/64 events (39%) and 14/43 AC-adjudicated attacks (33%), MRI was reviewed during adjudication. Retrospective analysis revealed new domain-specific T1 and T2 MRI lesions in 90% of adjudicated attacks. Increased mean sGFAP concentrations (>2-fold change) from baseline were observed in 56% of adjudicated attacks versus 14% of investigator-determined attacks rejected by the AC and 31% of participant-reported events determined not to be attacks.Conclusion:AC adjudication of NMOSD attacks according to predefined criteria appears robust. MRI lesion correlates and sGFAP elevations were found in most adjudicated attacks.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".