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Record W4391609148 · doi:10.1093/bjd/ljad498.030

525 - Real-world effectiveness of upadacitinib in moderate-to-severe atopic dermatitis (AD): Results from cross-sectional analyses of the CorEvitas AD Registry

2024· article· en· W4391609148 on OpenAlexaff
Jonathan I. Silverberg, Melinda Gooderham, Brian Calimlim, Ayman Grada, Yolanda Muñoz Maldonado, Alvin Li, Margaux M. Crabtree, Eric L. Simpson

Bibliographic record

VenueBritish Journal of Dermatology · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsProbity Medical ResearchQueen's University
Fundersnot available
KeywordsAtopic dermatitisMedicineDermatologyCross-sectional studyPathology

Abstract

fetched live from OpenAlex

Abstract Introduction/Background Upadacitinib is an oral Janus kinase inhibitor approved to treat moderate-to-severe atopic dermatitis (AD). While clinical trials have demonstrated its efficacy in treating the signs and symptoms of AD, less is known about its effectiveness in a real-world setting. Objectives This cross-sectional study describes the real-world clinical and patient-reported outcomes of adults with AD enrolled in the CorEvitas AD Registry and treated with upadacitinib for at least four or more weeks. Methods The CorEvitas AD Registry is a prospective, non-interventional registry of adults diagnosed with AD by a dermatologist or qualified dermatology practitioner. The current analysis included participants enrolled between July 21, 2020 through August 7, 2023 who were treated with upadacitinib for at least 4 weeks at the time of evaluation by their provider. Outcome measures included assessments of: skin clearance (Validated Investigators Global Assessment Scale for Atopic Dermatitis [vIGA-AD™], Eczema Area and Severity Index [EASI]); worst itch in the past 24 hours (Peak Pruritus Numeric Rating Scale [PP-NRS]); symptom frequency (Patient-Oriented Eczema Measure [POEM]); quality of life (Dermatologic Life Quality Index [DLQI]); and disease control (Atopic Dermatitis Control Tool [ADCT]). Outcomes were cross-sectionally summarized using data collected at the latest registry visit (Overall cohort), as well as 1 to less than 5 months (1-5 months) and 5-9 months following upadacitinib initiation (Month 1-5 cohort and Month 5-9 cohort, respectively). Subgroup analyses were also conducted based on prior use of biologics indicated for AD (bio-naïve, bio-experienced). Data were analyzed as observed with no imputation. Safety events were not assessed in this ­analysis. Results A total of 335 patients (mean age 45.6 years; 51.6% female; 64.2% White) were treated with upadacitinib (15 mg: n=221 [70.8%]; 30 mg: n=91 [29.2%]; median treatment duration: 6.9 months). Some patients reported concomitant use of topical corticosteroids (28.1%) and prior use of biologics indicated for AD (dupilumab: 45.4%; tralokinumab: 6.0%). For the Overall cohort, 57.3% had clear or almost clear skin (vIGA-AD 0/1). An EASI ≤3 was observed in 74.8% of patients and 45.3% reported no/minimal itch (PP-NRS 0/1); 40.9% had both EASI ≤3 and PP-NRS 0/1. Most patients (69.3%) reported that their AD was controlled (ADCT <7), 36.4% reported clear or almost clear disease (POEM 0–2), and 39.8% reported no impact of AD on their quality of life (DLQI 0/1). Similar results were observed for the Month 1-5 (n=144) and Month 5-9 (n=194) cohorts; results in bio-naïve and bio-experienced patients were comparable. Conclusions More than half of patients with ≥4 weeks of upadacitinib treatment had clear or almost clear skin and greater than two-thirds reported controlled disease, with similar results observed in both bio-naïve and bio-experienced patients. Over a third reported no/minimal symptom and disease burden. These findings suggest that low levels of disease severity are observed with real-world use of upadacitinib. Future analyses will aim to report changes in disease severity and burden due to persistent upadacitinib treatment.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.029
GPT teacher head0.343
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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