Allergen immunotherapy for atopic dermatitis: Systematic review and meta-analysis of benefits and harms
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD, eczema) is driven by a combination of skin barrier defects, immune dysregulation, and extrinsic stimuli such as allergens, irritants, and microbes. The role of environmental allergens (aeroallergens) in triggering AD remains unclear. OBJECTIVE: We systematically synthesized evidence regarding the benefits and harms of allergen immunotherapy (AIT) for AD. METHODS: As part of the 2022 American Academy of Allergy, Asthma & Immunology/American College of Allergy, Asthma and Immunology Joint Task Force on Practice Parameters AD Guideline update, we searched the MEDLINE, EMBASE, CENTRAL, CINAHL, LILACS, Global Resource for Eczema Trials, and Web of Science databases from inception to December 2021 for randomized controlled trials comparing subcutaneous immunotherapy (SCIT), sublingual immunotherapy (SLIT), and/or no AIT (placebo or standard care) for guideline panel-defined patient-important outcomes: AD severity, itch, AD-related quality of life (QoL), flares, and adverse events. Raters independently screened, extracted data, and assessed risk of bias in duplicate. We synthesized intervention effects using frequentist and Bayesian random-effects models. The GRADE approach determined the quality of evidence. RESULTS: Twenty-three randomized controlled trials including 1957 adult and pediatric patients sensitized primarily to house dust mite showed that add-on SCIT and SLIT have similar relative and absolute effects and likely result in important improvements in AD severity, defined as a 50% reduction in SCORing Atopic Dermatitis (risk ratio [95% confidence interval] 1.53 [1.31-1.78]; 26% vs 40%, absolute difference 14%) and QoL, defined as an improvement in Dermatology Life Quality Index by 4 points or more (risk ratio [95% confidence interval] 1.44 [1.03-2.01]; 39% vs 56%, absolute difference 17%; both outcomes moderate certainty). Both routes of AIT increased adverse events (risk ratio [95% confidence interval] 1.61 [1.44-1.79]; 66% with SCIT vs 41% with placebo; 13% with SLIT vs 8% with placebo; high certainty). AIT's effect on sleep disturbance and eczema flares was very uncertain. Subgroup and sensitivity analyses were consistent with the main findings. CONCLUSIONS: SCIT and SLIT to aeroallergens, particularly house dust mite, can similarly and importantly improve AD severity and QoL. SCIT increases adverse effects more than SLIT. These findings support a multidisciplinary and shared decision-making approach to optimally managing AD.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.033 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".