D.7 Efgartigimod impact on I-RODS daily activity assessment in chronic inflammatory demyelinating polyneuropathy: post hoc analysis of Registrational ADHERE Study
Bibliographic record
Abstract
Background: Efgartigimod, a human immunoglobulin (Ig)G1 antibody Fc fragment, blocks the neonatal Fc receptor, reducing IgGs involved in chronic inflammatory demyelinating polyneuropathy (CIDP), a rare, progressive, immune-mediated disease that can lead to irreversible disability. The multi-stage, double-blinded, placebo-controlled ADHERE (NCT04281472) trial assessed efgartigimod PH20 SC in participants with CIDP. Methods: Participants with active CIDP received open-label, weekly efgartigimod PH20 SC 1000 mg during ≤12-week run-in (stage-A). Responders were randomized (1:1) to weekly efgartigimod or placebo for ≤48 weeks (stage-B). This posthoc analysis evaluated changes from run-in baseline (study enrollment) to stage-B last assessment and items of the Inflammatory Rasch-built Overall Disability Scale (I-RODS). Results: Of 322 participants who entered stage-A, 221 were randomized and treated in stage-B, and 191/221 had data for run-in baseline and post–stage-B timepoints. Mean (SE) I-RODS change at stage-B last assessment vs run-in baseline was 5.7 (1.88) and -4.9 (1.82) in participants randomized to efgartigimod and placebo, respectively. 37/97 (38.1%) and 24/92 (26.1%) participants randomized to efgartigimod and placebo, respectively, experienced ≥4-point improvements in I-RODS score. Efgartigimod-treated participants improved ≥1 point in I-RODS items of clinical interest. Conclusions: Participants who received efgartigimod in stage-B experienced improvements in I-RODS score from study enrollment to stage-B last assessment.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".