Dupilumab shows long-term safety and efficacy in patients with moderate to severe atopic dermatitis enrolled in a phase 3 open-label extension study
Bibliographic record
Abstract
BACKGROUND: Significant unmet need exists for long-term treatment of moderate to severe atopic dermatitis (AD). OBJECTIVE: To assess the long-term safety and efficacy of dupilumab in patients with AD. METHODS: This ongoing, multicenter, open-label extension study (NCT01949311) evaluated long-term dupilumab treatment in adults who had previously participated in phase 1 through 3 clinical trials of dupilumab for AD. This analysis examined patients given 300 mg dupilumab weekly for up to 76 weeks at data cutoff (April 2016). Safety was the primary outcome; efficacy was also evaluated. RESULTS: Of 1491 enrolled patients (1042.9 patient-years), 92.9% were receiving treatment at cutoff. The safety profile was consistent with previously reported trials (420.4 adverse events/100 patient-years and 8.5 serious adverse events/100 patient-years), with no new safety signals; common adverse events included nasopharyngitis, conjunctivitis, and injection-site reactions. Sustained improvement was seen up to 76 weeks in all efficacy outcomes, including measures of skin inflammation, pruritus, and quality of life. LIMITATIONS: Lack of control arm, limited number of patients with 76 weeks or longer of treatment (median follow-up, 24 weeks), and patients not receiving the approved dose regimen of 300 mg every 2 weeks. CONCLUSION: The safety and efficacy profile from this study supports the role of dupilumab as continuous long-term treatment for patients with moderate to severe 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".