When does atopic dermatitis warrant systemic therapy? Recommendations from an expert panel of the International Eczema Council
Bibliographic record
Abstract
BACKGROUND: Although most patients with atopic dermatitis (AD) are effectively managed with topical medication, a significant minority require systemic therapy. Guidelines for decision making about advancement to systemic therapy are lacking. OBJECTIVE: To guide those considering use of systemic therapy in AD and provide a framework for evaluation before making this therapeutic decision with the patient. METHODS: A subgroup of the International Eczema Council determined aspects to consider before prescribing systemic therapy. Topics were assigned to expert reviewers who performed a topic-specific literature review, referred to guidelines when available, and provided interpretation and expert opinion. RESULTS: We recommend a systematic and holistic approach to assess patients with severe signs and symptoms of AD and impact on quality of life before systemic therapy. Steps taken before commencing systemic therapy include considering alternate or concomitant diagnoses, avoiding trigger factors, optimizing topical therapy, ensuring adequate patient/caregiver education, treating coexistent infection, assessing the impact on quality of life, and considering phototherapy. LIMITATIONS: Our work is a consensus statement, not a systematic review. CONCLUSION: The decision to start systemic medication should include assessment of severity and quality of life while considering the individual's general health status, psychologic needs, and personal attitudes toward systemic therapies.
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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 | 0.031 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".