Patient‐reported outcomes with subcutaneous immunoglobulin in chronic inflammatory demyelinating polyneuropathy: the PATH study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Chronic inflammatory demyelinating polyneuropathy (CIDP) causes weakness which adversely impacts function and quality of life (QOL). CIDP often requires long-term management with intravenous or subcutaneous immunoglobulin. The Polyneuropathy and Treatment with Hizentra® (PATH) study showed that subcutaneous immunoglobulin (SCIG) was efficacious in CIDP maintenance. Here, patient-reported outcomes in patients on SCIG are assessed. METHODS: Subjects stabilized on intravenous immunoglobulin were randomly allocated to receive weekly 0.2 or 0.4 g/kg bodyweight of 20% SCIG (IgPro20) or placebo. Overall QOL/health status was assessed using the EuroQoL 5-Dimension (EQ-5D) health profile and visual analog scale, treatment satisfaction was assessed with the Treatment Satisfaction Questionnaire for Medicine (TSQM) and work-related impact was assessed with the Work Productivity and Activity Impairment Questionnaire for General Health (WPAI-GH). The EQ-5D health profile was assessed in terms of the percentage of subjects maintained or improved at week 25 of SCIG therapy on each of the EQ-5D domains versus baseline after intravenous immunoglobulin stabilization. TSQM and WPAI-GH were assessed by median score changes from baseline to week 25. RESULTS: In total, 172 subjects were randomized to placebo (n = 57), 0.2 g/kg IgPro20 (n = 57) and 0.4 g/kg IgPro20 (n = 58). Significantly higher proportions of IgPro20-treated subjects improved/maintained their health status on the EQ-5D usual activities dimension, and in additional dimensions (mobility and pain/discomfort) in sensitivity analyses. TSQM and WPAI-GH scores were more stable with IgPro20 treatment compared with placebo. CONCLUSIONS: IgPro20 maintained or improved QOL in most subjects with CIDP, consistent with the PATH study findings that both IgPro20 doses were efficacious in maintaining CIDP.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".