Which outcomes have been measured in hand eczema trials? A systematic review
Bibliographic record
Abstract
The considerable heterogeneity of outcomes and measurement instruments in hand eczema trials substantially limits the evidence synthesis concerning therapeutic and preventive interventions. Therefore, the Hand Eczema Core Outcome Set (HECOS) initiative is developing a core outcome set for future trials. The first objective was to identify outcomes that were measured in previous trials, to group them in domains, and to identify their measurement instruments. We conducted a systematic review of controlled and randomized controlled hand eczema trials published since 2000. Sixty-one eligible studies were identified. Each assessed one or more of 47 outcomes in the "skin" domain. Eighteen trials (30%) additionally focused on preventive behaviour in risk occupations. Quality of life was measured in 13 studies (21%). Thirty-two distinct named instruments were applied, but 223 measurements (62%) were conducted with unnamed instruments. Only 32 studies (52%) defined a primary outcome. Twenty-nine trials (48%) provided some information on adverse events, but none gave any references concerning relevant methods. Our review confirms the need to harmonize outcome measurements in hand eczema trials. The findings form the basis for a consensus process to generate a core outcome set to improve the explanatory power and comparability of future hand eczema studies.
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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 | 0.062 | 0.240 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.011 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".