Predictors of response to opicinumab in acute optic neuritis
Bibliographic record
Abstract
Abstract Objective The objective of this study was to evaluate prespecified and post hoc analyses in RENEW subgroups to identify participants more likely to benefit from opicinumab. Methods RENEW assessed the efficacy/safety of opicinumab versus placebo in participants with a first unilateral acute optic neuritis ( AON ) episode. Difference in visual evoked potential ( VEP ) latency of the affected eye at 24 weeks versus the fellow eye at baseline was the primary endpoint. Interactions between the primary endpoint and prespecified baseline variables (including age, timing of treatment initiation, and visual impairment) using the median as cut‐off were evaluated in the per protocol population using analysis of covariance ( ANCOVA ); subgroups based on preexisting brain T2 lesion volume were also analyzed. Interactions between the primary endpoint and retinal ganglion cell layer/inner plexiform layer ( RGCL / IPL ) and retinal nerve fiber layer ( RNFL ) thickness were assessed post hoc as was weight gain by treatment. Results Treatment benefit of opicinumab ( n = 33) over placebo ( n = 36) on the primary endpoint was greatest in participants older than the median age at baseline (≥33 years); the difference versus placebo for baseline age ≥33 years was −14.17 msec [ P = 0.01] versus −0.89 msec for baseline age <33 years, [ P = 0.87]). Post hoc analysis showed that VEP latency recovery was significantly associated with less RGCL / IPL thinning ( P = 0.0164), occurring early on. Interpretation Age was the strongest prespecified baseline characteristic associated with a treatment effect of opicinumab. A strong association between VEP latency recovery at week 24 and early RGCL / IPL preservation was observed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".