A Review of Existing and New Treatments for the Management of Hand Eczema
Bibliographic record
Abstract
Hand eczema is a chronic condition that affects an estimated 14.5% of the general population. It has severe quality of life ramifications in those that struggle with it, including days missed from work or school, productivity loss and impaired work functioning. For years, the standard of care included topical moisturizing creams, topical steroids and more recently systemic agents. As new therapeutic targets emerge and recent advances are being developed, it is now more possible than ever that hand eczema can be managed via the underlying mechanisms. A review of the literature was conducted to identify current treatment options for hand eczema and chronic hand eczema. The terms 'hand eczema', 'hand dermatitis' were used to search PubMed, CENTRAL and Embase. To identify new therapies still undergoing investigation, we used the terms 'hand eczema', 'hand dermatitis', 'atopic dermatitis', and 'vesicular eczema of hands and/or feet' to search Clinicaltrials.gov for all studies until December 2022. There were 56 ongoing clinical trials identified for pharmacological treatments for hand eczema on Clinicaltrials.gov from 2000 - 2022, with 16 that are new or ongoing. These included studies for dupilumab, ruxolitinib, delgocitinib (LEO124249), gusacitinib (ASN002), AFX 5931, and roflumilast (ARQ-252). Two major classes of drugs emerging for the treatment of hand eczema include IL-4/IL-13 inhibitors and JAK inhibitors. With the increase in efficacy seen with these new drugs, we are also noting improved adverse effect profiles, making them attractive options to add to a clinician's management toolbox for patients with hand eczema.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".