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Record W4391033331 · doi:10.25251/skin.8.supp.356

Apremilast for the Treatment of Psoriasis in Special Areas in Pediatric Patients in the SPROUT Study

2024· article· en· W4391033331 on OpenAlexaff
Loretta Fiorillo, Emily Becker, Anna Belloni Fortina, Susana Armesto, Peter Maes, Apostolos Kontzias, Maria Paris, Wendy Zhang, Zuoshun Zhang, Lisa M. Arkin

Bibliographic record

VenueSKIN The Journal of Cutaneous Medicine · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsStollery Children's HospitalUniversity of Alberta
FundersAmgen
KeywordsApremilastPsoriasisMedicineDermatologyIntensive care medicinePsoriatic arthritis

Abstract

fetched live from OpenAlex

Introduction & Objective: Psoriasis in special areas is difficult to treat and causes significant disease burden. Approved systemic therapies for moderate to severe plaque psoriasis in pediatric patients are limited and require subcutaneous injection. Apremilast, a unique oral immunomodulator that inhibits phosphodiesterase-4, is approved in multiple countries for use in adults with psoriasis, regardless of severity. In this study, the efficacy of apremilast for psoriasis in special areas in pediatric patients was assessed over 16 weeks. Materials & Methods: SPROUT (NCT03701763) is a phase 3, randomized, double-blind, placebo-controlled study in patients 6-17 years with moderate to severe plaque psoriasis (Psoriasis Area and Severity Index ≥12, body surface area ≥10%, and static Physician Global Assessment [sPGA] ≥3) inadequately controlled by/inappropriate for topical therapy. Patients were stratified by age and randomized 2:1 to receive apremilast (weight-based 20 mg or 30 mg twice-a-day) or placebo for 16 weeks, then apremilast through week 52. Scalp Physician Global Assessment (ScPGA) response, modified sPGA of genitalia (sPGA-G) response, Whole Body Itch-Numeric Rating Scale (WBI-NRS) response, and change from baseline in Children’s Dermatology Life Quality Index (CDLQI) were assessed through week 16. Results: Of 245 randomized patients (apremilast: 163; placebo: 82), 101 (41.2%) were 6-11 years and 144 (58.8%) were 12-17 years; 120 (49.0%) patients weighed ≥20 to <50 kg and 125 (51.0%) weighed ≥50 kg. At baseline, 81.0% of the patients treated with apremilast and 84.1% of patients treated with placebo had moderate to severe scalp psoriasis (ScPGA ≥3). Significantly more patients achieved ScPGA response at week 16 with apremilast vs placebo (36.4% vs 18.8%; P=0.0091). At baseline, 110 patients (44.9%; 45.4% apremilast and 43.9% placebo) had moderate to severe genital psoriasis (sPGA-G ≥3). Achievement of sPGA-G response at week 16 was numerically greater with apremilast vs placebo (39.2% vs 25.0%), although not significant, possibly due to small sample size (apremilast: n=74; placebo: n=36). Significantly more patients achieved WBI-NRS response at week 16 with apremilast vs placebo (52.0% vs 32.1%; P=0.0110). Greater improvements in CDLQI were seen at week 16 with apremilast vs placebo (least-squares mean change from baseline −5.1 vs −3.2; P=0.0009). Adverse events were consistent with the known apremilast safety profile. In 21 patients vaccinated during the study (including for COVID-19, influenza, diphtheria, pertussis, tetanus, meningococcus, and hepatitis B), no new safety issues occurred. Conclusions: Apremilast significantly improved scalp psoriasis, itch, and quality of life in pediatric patients with moderate to severe psoriasis. At week 16, patients with moderate to severe genital psoriasis showed a trend toward improvement, although not significant due partially to the sample size.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.265
Teacher spread0.248 · 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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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