Validation of the Investigator Global Assessment of Chronic Hand Eczema (IGA–CHE): a new clinician reported outcome measure of CHE severity
Bibliographic record
Abstract
The Investigator Global Assessment of Chronic Hand Eczema (IGA-CHE) is a novel Clinician-Reported Outcome measure that allows investigators to assess cross-sectional CHE global disease severity using clinical characteristics of erythema, scaling, lichenification/hyperkeratosis, vesiculation, oedema, and fissures as guidelines for overall severity assessment. This study aimed to evaluate the psychometric properties of the IGA-CHE for use as an outcome measure in CHE clinical trials and clinical practice. Psychometric analyses were performed using data from a sample of 280 patients with moderate to severe CHE from a phase 3 trial of delgocitinib cream, pooled across treatment groups. Test-retest reliability results were moderate to strong with kappa coefficients ranging from 0.63 to 0.76. Correlations with measures assessing related concepts were moderate or strong (range 0.65-0.72) and exceeded a priori hypotheses, providing evidence of convergent validity. Known-groups validity was supported by statistically significant differences between severity groups (< 0.001). Within-group effect sizes were consistently larger for improved groups compared to stable groups, providing evidence of ability to detect change. Anchor-based analyses generated within-subject meaningful change estimates ranging from - 0.8 to - 2.3. A correlation weighted average suggested a single value of - 1.7 in change from baseline. These findings provide evidence the IGA-CHE scale has strong reliability, construct validity, and ability to detect change, supporting its use as an endpoint in CHE clinical trials and clinical practice. Based on the evidence, 2-level changes in IGA-CHE score are considered a conservative meaningful change threshold; however, findings also indicate 1-level change in IGA-CHE scores reflects a clinically meaningful improvement for patients.Clinical trial registration: NCT04871711.
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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 | 0.025 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".