The role of interleukin-13 in the management of atopic dermatitis: An expert consensus panel
Bibliographic record
Abstract
Atopic dermatitis is a chronic inflammatory skin condition driven by immune dysregulation, with interleukin-13 playing a central role in its pathogenesis. Recent advances in targeted biologic therapies have shown promising results in treating moderate-to-severe atopic dermatitis. A comprehensive literature review of PubMed and Google Scholar was conducted to identify studies related to interleukin-13 inhibition in atopic dermatitis. An expert panel reviewed and graded the evidence using Strength of Recommendation Taxonomy criteria and utilized a modified Delphi process to formulate consensus statements on the role of interleukin-13 inhibitors. Based on selected literature, the panel developed 14 consensus statements, all receiving unanimous approval. Key findings include the rapid efficacy, sustained benefits, and favorable safety profiles of interleukin-13 inhibitors. Differences between available interleukin-13 inhibitors included pain of injection, speed of onset, durability of efficacy, and number of injections needed to maintain efficacy. Interleukin-13 plays a pivotal role in atopic dermatitis pathogenesis, driving inflammation, pruritus, and barrier dysfunction. Targeted therapies, including interleukin-13 inhibitors, provide rapid, durable, and safe options for managing moderate-to-severe atopic dermatitis. This consensus highlights interleukin-13 inhibition as a cornerstone in advancing atopic dermatitis treatment strategies, offering improved patient outcomes and quality of life.
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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 | 0.090 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| 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".