Safety and Efficacy of Anti-OX40 Therapies in Atopic Dermatitis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract: Atopic dermatitis (AD) is a chronic inflammatory skin disorder that significantly impacts patients’ quality of life. Novel biological agents targeting the OX40 pathway have shown promise in refractory cases. We aimed to systematically evaluate the efficacy and safety of anti-OX40 therapies (amlitelimab, rocatinlimab, and telazorlimab) in moderate-to-severe AD. We systematically searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) databases up to January 2025 for clinical trials comparing anti-OX40 therapies with placebo in patients with AD. This study followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Five randomized clinical trials were included, comprising 1118 patients, of whom 857 (76.6%) received one of the anti-OX40 therapies. Both high-dose (mean difference [MD] = −17.33; 95% confidence interval [CI] = −23.79 to −10.87; P < 0.001) and low-dose (MD = −16.35; 95% CI = −27.42 to −5.28; P = 0.004) regimens significantly improved the SCORing AD, and multiple other outcomes also showed statistically significant improvements, including reductions in the mean Eczema Area and Severity Index score and body surface area affected by the disease. The incidence of any treatment-emergent adverse event was not statistically significant for either the high-dose group (risk ratio [RR] = 1.14; 95% CI = 0.82–1.59; P = 0.443) or the low-dose group (RR = 1.10; 95% CI = 0.84–1.45; P = 0.486). In conclusion, anti-OX40 therapies demonstrate clinically meaningful efficacy and an acceptable safety profile for moderate-to-severe AD, offering a potential alternative for patients with inadequate responses to current treatments. Further research is warranted to confirm these results and to refine optimal dosing strategies.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".