<i>Letter:</i> Tralokinumab for the Treatment of Chronic Hand Eczema: A Retrospective Case Series with Long-Term Follow-up
Bibliographic record
Abstract
To the Editor:Chronic hand eczema (CHE) has a significant impact on the quality of life despite the limited body surface area affected.Management of CHE poses several challenges, such as lack of universally acceptable therapies and the need for long-term treatment.The current therapeutic ladder of CHE mirrors that of atopic dermatitis (AD) in the pre-biological era. 1 Recently approved therapies include dupilumab, an interleukin (IL)-4 and 13 blocker for atopic CHE, and delgocitinib, a topical pan-JAK inhibitor (JAKi).Tralokinumab, a monoclonal antibody selectively targeting IL-13, is approved for moderate to severe AD.Data on its use exclusively for CHE are limited.2 We present this series of 6 CHE patients treated with tralokinumab with long-term follow-up.A retrospective chart review of CHE patients treated with tralokinumab from January 2022 to December 2024 was performed.Search words used in clinic notes were "chronic hand eczema" and "tralokinumab."Patients with a minimum follow-up of 16 weeks were included.Clinical photographs and Hand Eczema Severity Index (HECSI) scores at baseline, weeks 16 and 52 (if available) were compared.We identified 6 adult CHE patients on tralokinumab (4 males, 2 females, mean age 45.5 -20.5 years, Table 1).Four patients were non-atopic, of whom 2 had additional foot involvement.Two patients had atopic CHE with mild concomitant AD.Three patients had a mixed pattern and 3 vesicular CHE.A skin biopsy was performed in 4 patients.Patch testing was negative in the 4 patients tested.At 16 weeks, 3 (50%) achieved HECSI 90, and 3 (50%) had achieved HECSI 75.Long-term data was available for 4 patients who achieved HECSI 100 at week 52 and continued to receive tralokinumab.The longest follow-up is 28 months.One patient was No funding was received for this article.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".