Analysis of relapse by inflammatory Rasch‐built overall disability scale status in the <scp>PATH</scp> study of subcutaneous immunoglobulin in chronic inflammatory demyelinating polyneuropathy
Bibliographic record
Abstract
Clinical trials in chronic inflammatory demyelinating polyneuropathy (CIDP) often assess efficacy using the ordinal Inflammatory Neuropathy Cause and Treatment (INCAT) disability score. Here, data from the PATH study was reanalyzed using change in Inflammatory Rasch-built Overall Disability Scale (I-RODS) to define CIDP relapse instead of INCAT. The PATH study comprised an intravenous immunoglobulin (IVIG) dependency period and an IVIG (IgPro10 [Privigen]) restabilization period; subjects were then randomized to weekly maintenance subcutaneous immunoglobulin (SCIG; IgPro20 [Hizentra]) 0.2 g/kg or 0.4 g/kg or placebo for 24 weeks. CIDP relapse was defined as ≥1-point deterioration in adjusted INCAT, with a primary endpoint of relapse or withdrawal rates. This retrospective exploratory analysis redefined relapse using I-RODS via three different cut-off methods: an individual variability method, fixed cut-off of ≥8-point deterioration on I-RODS centile score or ≥4-point deterioration on I-RODS raw score. Relapse or withdrawal rates were 47% for placebo, 34% for 0.2 g/kg IgPro20 and 19% for 0.4 g/kg IgPro20 using the raw score; 40%, 28% and 15%, respectively using the centile score, and 49%, 40% and 27%, respectively using the individual variability method. IgPro20 was shown to be efficacious as a maintenance therapy for CIDP when relapse was defined using I-RODS. A stable response pattern was shown for I-RODS across various applied cut-offs, which could be applied in future clinical trials.
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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 | 0.017 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".