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Record W4411733287 · doi:10.1093/bjd/ljaf085.016

O01 The UK–Irish Atopic Eczema Systemic Therapy Register (A-STAR): a pilot descriptive analysis of healthcare resource use, costs and health-related quality of life in patients on systemic treatments for atopic eczema

2025· article· en· W4411733287 on OpenAlexaff
Carlos Chivardi, Elizaveta Gribaleva, Bolaji Coker, Man Fung Tsoi, Rebecca Carroll, David Prieto-Merino, Manisha Baden, Paula Beattie, Sara Brown, Tim Burton, Ross Hearn, John R Ingram, Alan D. Irvine, G.A. Johnston, Irene Man, Graham S. Ogg, Mandy Wan, Richard B. Warren, Richard Woolf, Nick J. Reynolds, Michael R. Ardern‐Jones, Carsten Flohr, Andrea Manca

Bibliographic record

VenueBritish Journal of Dermatology · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineSystemic therapyRegister (sociolinguistics)IrishQuality of life (healthcare)Health careFamily medicineNursingInternal medicine

Abstract

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Abstract Clinical management of moderate-to-severe atopic eczema (AE) is complex, involving the use of several therapies. Some novel systemic immunomodulatory medications are effective but costly, while conventional systemic therapies have lower costs but require frequent monitoring due to their safety profiles. Novel systemic therapies for AE have been assessed in randomized controlled trials, but their evidence is incomplete to inform real-world practice and value-for-money considerations. The UK–Irish Atopic Eczema Systemic Therapy Register (A-STAR) was established to address the need for real-world evidence and to capture comprehensive health economics data surrounding the use of systemic therapies to manage moderate-to-severe AE. The aim of the current study was to describe healthcare resource utilization and patient-reported health-related quality of life (HRQoL) in a cohort of patients from A-STAR during a 1-year follow-up period and to evaluate the quality of the data collected in a real-world setting. The A-STAR register is a multicentre prospective register recruiting paediatric (< 16 years old) and adult (≥ 16 years old) patients with AE initiating or switching to systemic immunomodulatory therapy. Healthcare resource utilization data including general practitioner (GP) visits, accident and emergency attendance, hospitalizations, specialist consultations and systemic therapy were collected and valuated using national average unit costs. EuroQol-5D was used to measure HRQoL. In total 120 A-STAR participants (92 adults and 28 children) with at least 1 year of follow-up were included in this pilot study. Adults showed higher healthcare utilization than children. For adults, the mean costs per visit included accident and emergency attendance (£120.41), GP appointments (£111.15) and outpatient specialist visits (£205.17). Children had lower healthcare utilization and costs per visit: accident and emergency attendance (£84.29), GP appointments (£78.46) and outpatient specialist visits (£121.00). All participants required outpatient dermatology visits, with a mean cost of £551 for adults and £777 for children. Both groups received systemic therapy, and adults incurred higher costs (mean £25 523, SD £24 424) than children (mean £20 242, SD £18 994). The average EuroQol-5D scores improved in both groups from baseline to 1 year, from 0.61 (SD 0.31) to 0.77 (SD 0.24) in adults, and from 0.48 (SD 0.37) to 0.75 (SD 0.27) in children. In this pilot descriptive analysis, patients with AE receiving systemic treatment were found to accrue substantial healthcare resource use and tended to have an improvement in their HRQoL within the observed period. Registers like A-STAR hold promise in health research, aiding policymakers in formulating treatment pathways for patients and optimizing sparse data to enhance overall outcomes. These insights are crucial for shaping future register data collection efforts and advancing healthcare decision making, including by the UK National Institute for Clinical and Care Excellence.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.060
GPT teacher head0.332
Teacher spread0.272 · 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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Citations0
Published2025
Admission routes1
Has abstractyes

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