Ocular Adverse Events in Patients with Atopic Dermatitis Treated with Upadacitinib: A Real-Life Experience
Bibliographic record
Abstract
Background: Dupilumab, an interleukin (IL)-4 receptor-α inhibitor that blocks IL-4 and IL-13 signaling pathways, is an effective and well-tolerated therapy for moderate-to-severe atopic dermatitis (AD). However, an increased incidence of dupilumab-associated conjunctivitis has been reported in patients treated with dupilumab. In contrast, upadacitinib, a selective Janus kinase 1 inhibitor, is reported to have lower incidence of conjunctivitis than dupilumab. Objective: The aim of this retrospective study was to investigate ocular adverse events in adult patients with moderate-to-severe AD treated with upadacitinib after discontinuing treatment with dupilumab. Methods: In total, 33 patients were examined at the start of treatment with upadacitinib after discontinuation of dupilumab, then again after 4 weeks and every 12 weeks up to a maximum of 72 weeks. Results: Among the patients in the study, 14 had developed dupilumab-associated conjunctivitis during dupilumab treatment and had complete resolution of ocular symptoms after the switch to upadacitinib within the 1-month follow-up visit. In addition, only 1 patient treated with upadacitinib developed an episode of conjunctivitis. This condition was of mild severity and it spontaneously resolved quickly. Interestingly, this patient had no history of dupilumab-associated conjunctivitis. Conclusions: All patients who developed dupilumab-associated conjunctivitis experienced complete remission on upadacitinib and only 3% of the patients in our sample developed conjunctivitis after the start of treatment with upadacitinib. In light of this, upadacitinib appears to be a prudent and safe treatment option for AD patients with uncontrolled ocular symptoms associated with dupilumab therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".