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Record W4409476142 · doi:10.1007/s13555-025-01395-1

Complete/Near-Complete Itch Response Observed in Patients with Moderate-to-Severe Atopic Dermatitis Initiating Dupilumab: 3-Year, Real-World, Interim Data from the PROSE Registry

2025· article· en· W4409476142 on OpenAlexaffabout
Neal Bhatia, Charles Lynde, Luz Fonacier, Liyang Shao, Kwinten Bosman, Andrew Korotzer

Bibliographic record

VenueDermatology and Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsLynde Centre for DermatologyUniversity of Toronto
FundersRegeneron PharmaceuticalsSanofi
KeywordsDupilumabAtopic dermatitisInterimDermatologyMedicineInterim analysisClinical trialInternal medicineGeography

Abstract

fetched live from OpenAlex

Atopic dermatitis (AD) is a chronic, relapsing disease that can start at any age and has a significant negative impact on quality of life, including a significant itch burden. Here we report the proportion of patients in a real-world study achieving a complete/almost complete resolution of itch, as measured by the Peak Pruritus Numeric Rating Scale (PP-NRS) and improvement in overall disease severity score (ODS), in patients aged ≥ 12 years with moderate-to-severe AD up to 3 years after commencing dupilumab treatment. PROSE is an ongoing, prospective, observational, multicenter registry in the USA and Canada, collecting real-world data from patients aged ≥ 12 years with moderate-to-severe AD who initiated dupilumab in accordance with country-specific prescribing information. Assessments include patient-reported PP-NRS (range 0–10) and clinician-measured ODS score (range 0–4). A total of 857 patients were enrolled, of whom 42% were male and 6.4% were adolescents aged ≥ 12 to < 18 years. The mean [standard deviation (SD)] age was 40.1 (17.9) years, and the duration of AD was 17.4 (16.2) years. The subsequent mean (SD) duration of dupilumab treatment was 23.1 (13.7) months. The proportion of patients achieving complete/almost complete itch resolution (PP-NRS score of 0 or 1) improved consistently over time, from 2.7% (17/622) of patients at baseline to 56.3% (58/103) at 3 years. Additionally, by year 3, 65.1% (54/83) of patients had an ODS score of no/minimal disease (score of 0 or 1), versus 2.2% (19/852) at baseline. In this real-world setting of the PROSE registry, adult and adolescent patients with moderate-to-severe AD followed up for up to 3 years after the initiation of dupilumab treatment experienced sustained and substantial improvement in pruritus and ODS, using the stringent endpoints of PP-NRS 0 or 1 and ODS 0 or 1. ClinicalTrials.gov identifier: NCT03428646. Atopic dermatitis (AD) is a long-term condition with rashes, inflammation and intense itching that disturbs sleep and daily activities. Dupilumab is used to treat AD when topical medications are not adequate. Our aim was to find out how many patients showed no or minimal itch and AD severity when patients use dupilumab over the long term in the real world. The PROSE real-world registry collected information on 857 adults and adolescents with AD who were prescribed dupilumab by their doctors. Patients in the registry reported their itch weekly on a scale from 0 (no itch) to 10 (worst possible itch). At the study start, and up to 36 months later, their doctor graded the severity of their AD from 0 (no disease) to 4 (severe disease). We measured how many PROSE patients had no/minimal itch and AD severity (in both cases, scores of 0 or 1) for up to 3 years after they started dupilumab treatment. At the study start, 2.7% of the patients had no or minimal itch. For those patients still being observed after 36 months (about 12% of the starting sample), 56.3% of the patients had no or almost no itch; the severity of AD improved similarly. These results show that many patients with AD receiving dupilumab can experience complete or almost complete itch and/or AD relief, although other medications could also have helped these patients improve. Our results are useful for doctors treating AD.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.305
Teacher spread0.250 · 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 teacher head, 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".

Quick stats

Citations5
Published2025
Admission routes2
Has abstractyes

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