Prevalence and Characteristics of Dupilumab-Induced Ocular Surface Disease in Adults With Atopic Dermatitis
Bibliographic record
Abstract
PURPOSE: Dupilumab-induced ocular surface disease (DIOSD) is a common reaction among patients treated for atopic dermatitis. This study aimed to identify the clinical characteristics, associated risk factors, treatment strategies, and long-term outcomes of DIOSD. METHODS: We conducted a multicenter retrospective cohort study of consecutive adult outpatients treated with dupilumab for moderate-to-severe atopic dermatitis from 2017 through 2021 at 2 tertiary care centers. We used stepwise multivariable logistic regression to assess the association between patient characteristics and development of DIOSD. RESULTS: Among 210 patients treated with dupilumab, 37% (n = 78) developed DIOSD over the 52-week follow-up period. Vision-threatening complications including corneal scarring and cicatricial ectropion were noted in 1% (n = 3) of patients. Clinical features were blepharoconjunctivitis (68%, n = 53), burning/stinging/dryness (14%, n = 29), epiphora (13%, n = 10), pruritus (13%, n = 10), blurred vision (3%, n = 2), and photophobia (1%, n = 1). DIOSD was associated with a history of asthma (odds ratio: 2.94, 95% confidence interval: 1.26-6.87, P = 0.01) and a family history of atopic dermatitis (odds ratio: 2.58, 95% confidence interval: 1.08-6.17, P = 0.03). Interventions were initiated for 63% of patients with DIOSD, with artificial tears (56%) and corticosteroid drops (29%) most commonly used. Dupilumab was discontinued because of DIOSD in 4% of patients. CONCLUSIONS: DIOSD is a common adverse event that is usually mild but may lead to treatment interruption and vision-threatening complications. A personal history of asthma and family history of atopic dermatitis may be associated with a higher risk of developing DIOSD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".