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Record W4386153609 · doi:10.1007/s40257-023-00810-7

Interpreting the Relationship Among Itch, Sleep, and Work Productivity in Patients with Moderate-to-Severe Atopic Dermatitis: A Post Hoc Analysis of JADE MONO-2

2023· article· en· W4386153609 on OpenAlexaff
Gil Yosipovitch, Melinda Gooderham, Sonja Ständer, Luz Fonacier, Jacek C. Szepietowski, Mette Deleuran, Giampiero Girolomoni, John Su, Andrew G. Bushmakin, Joseph C. Cappelleri, Claire Feeney, Gary Chan, Andrew Thorpe, Hernán Valdez, Pinaki Biswas, Ricardo Rojo, Marco DiBonaventura, Daniela E. Myers

Bibliographic record

VenueAmerican Journal of Clinical Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsSKiN Health
FundersPfizer
KeywordsMedicineAtopic dermatitisPost-hoc analysisJADE (particle detector)DermatologyPost hocSleep (system call)Work productivityProductivityInternal medicine

Abstract

fetched live from OpenAlex

Abrocitinib, an oral, once-daily Janus kinase 1-selective inhibitor, improved itch severity, sleep, and work productivity versus placebo in patients with moderate-to-severe atopic dermatitis. The aim of this study was to investigate relationships among itch, sleep, and work productivity in the phase III JADE MONO-2 clinical trial. A repeated-measures longitudinal model was used to examine relationships between itch (using the Peak Pruritus Numerical Rating Scale [PP-NRS] or Nighttime Itch Scale [NTIS]) and sleep disturbance/loss (using the Patient-Oriented Eczema Measure sleep item and SCORing AD Sleep Loss Visual Analog Scale) and, separately, between itch and work productivity (using the Work Productivity and Activity Impairment-Atopic Dermatitis Version 2.0 questionnaire). Mediation modelling was used to investigate the effect of treatment (abrocitinib vs placebo) on work impairment via improvements in itch and sleep. The relationships between itch/sleep and itch/work productivity were approximately linear. PP-NRS scores of 0, 4–6, and 10 were associated with 0 days, 3–4 days, and 7 days per week of disturbed sleep, respectively. PP-NRS or NTIS scores of 0–1, 4–5, and 10 were associated with 0–10%, 20–30%, and >50% overall work impairment, respectively. Seventy-five percent of the effect of abrocitinib on reducing work impairment was indirectly mediated by improvement in itch, followed by sleep. These results quantitatively demonstrate that reducing itch severity is associated with improvements in sleep and work productivity. Empirical evidence for the mechanism of action of abrocitinib showed that itch severity is improved, which reduces sleep loss/sleep disruption and, in turn, improves work productivity. NCT03575871 Atopic dermatitis (AD), also called atopic eczema, is a common skin disease that is associated with itch and reduced quality of life. Abrocitinib, a recently approved medicine for AD, was shown in clinical trials to improve itch, which is considered the most bothersome symptom to people with AD. Abrocitinib also improved sleep outcomes and work productivity in people with moderate or severe AD. It is unknown if improvement in itch can lead to improvement in sleep and work productivity. We analyzed data from the JADE MONO-2 study, which included 391 people who received treatment with abrocitinib or placebo for 12 weeks. We used mathematical modelling to study relationships between itch and sleep or work productivity. We also wanted to study if the improvements in itch and sleep with abrocitinib treatment had an impact on work productivity. We found that a relationship existed between itch, sleep disturbance, and work impairment; as itch improved, so too did sleep disturbance and work impairment. When people were treated with abrocitinib, they experienced relief from itch, which improved sleep, which in turn reduced work productivity loss. Larger and longer studies are needed to confirm these results. This analysis further informs the expectations of patients with moderate or severe AD as it relates to progression of symptom relief after treatment with abrocitinib.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.009
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.322
Teacher spread0.303 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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