Systemic Therapy for Atopic Dermatitis in Older Adults and Adults With Comorbidities: A Scoping Review and International Eczema Council Survey
Bibliographic record
Abstract
BACKGROUND: Clinical trials of systemic therapies for atopic dermatitis (AD) often exclude patients based on age and comorbidities. OBJECTIVES: We conducted a scoping review of observational studies and survey of International Eczema Council (IEC) members on the treatment of AD in patients with liver disease, renal disease, viral hepatitis, HIV, or history of malignancy. METHODS: We searched MEDLINE via Ovid, Embase via Ovid, and Web of Science from inception to September 14, 2020. We mapped the available evidence on the use of cyclosporine, methotrexate, azathioprine, mycophenolate, systemic corticosteroids, and dupilumab for AD in older adults (≥65 years) and adults with the previously mentioned comorbidities. We surveyed IEC members on their preferred systemic medications for each patient population. RESULTS: We identified 25 studies on the use of systemic medications in special populations of adults with AD. Although IEC members preferred dupilumab as the first-line systemic agent across all special populations, many could not identify viable third-line systemic therapy options for some populations. CONCLUSIONS: Data on systemic therapy for AD for older adults and adults with comorbidities are limited. Although IEC members' access to systemic therapies differs geographically, expert opinion suggests that dupilumab is preferred for those patients.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".