Baseline Demographics and Severity and Burden of Atopic Dermatitis in Adult Patients Initiating Dupilumab Treatment in a Real-World Registry (PROSE)
Bibliographic record
Abstract
Introduction: Dupilumab was initially approved in 2017 as the first biologic therapy for atopic dermatitis (AD). We characterized adults with AD initiating dupilumab in a real-world setting in the USA/Canada. Methods: PROSE is an ongoing, longitudinal, prospective, observational, multicenter registry of patients with AD initiating dupilumab per country-specific prescribing information. We report baseline data (day of first dupilumab injection) for patients enrolled from April 2018 through July 2019. Results: Among 315 patients (mean age 42.5 years, 55.2% female), the median AD duration was 17.0 years; 65.4% reported a history of type 2 inflammatory comorbidities (e.g., allergic rhinitis, asthma), and 93.3% reported treatment(s) for AD in the previous year, including topical corticosteroids (90.8%), systemic corticosteroids (36.2%), and nonsteroidal systemic therapies (14.0%). In total, 89.2% had an Overall Disease Severity score of 3 (moderate) or 4 (severe). Other mean disease severity scores included the following: Eczema Area and Severity Index 16.9 (range 0–72), body surface area affected 26.8%, Patient-Oriented Eczema Measure 18.5 (range 0–28), Dermatology Life Quality Index 12.7 (range 0–30), and pruritus Numerical Rating Scale score 6.9 (range 0–10). Conclusion: Patients initiating dupilumab have longstanding moderate-to-severe AD with significant disease burden and frequent type 2 comorbidities.
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 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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".