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Record W2892779110 · doi:10.1080/09546634.2018.1530439

Pharmacokinetic disposition of topical phosphodiesterase-4 inhibitor E6005 in patients with atopic dermatitis

2018· article· en· W2892779110 on OpenAlexfundno aff
Yasumi Kitahara, Seiichiro Hojo, Maiko Nomoto, Daisuke Onozuka, Masutaka Furue, Akihito Hagihara

Bibliographic record

VenueJournal of Dermatological Treatment · 2018
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsnot available
FundersEisai Canada
KeywordsMedicineAtopic dermatitisPharmacokineticsAdverse effectIncidence (geometry)DrugDermatologyLogistic regressionMetaboliteInternal medicineClinical significancePharmacology

Abstract

fetched live from OpenAlex

Background: A novel topical phosphodiesterase-4 inhibitor E6005 shows potential as effective treatment option for atopic dermatitis (AD); however, systemic exposure may cause potentially undesirable adverse reactions. In this study, we evaluated the relationship between the systemic exposure of E6005 and clinical parameters including skin condition and the incidence of AEs in patients with AD.Methods: The association analysis used the clinical data obtained in a previously conducted clinical study with topical E6005 in adult patients with AD. To estimate associations with drug exposure, generalized estimating equation logistic regression models were used, along with clinical data and plasma concentrations of M11, the major metabolite of E6005 (as an indicator for E6005 exposure).Results: The metabolite M11 was detected in 62 of 221 plasma samples from 72 subjects. From association analysis, SCORAD-A obtained prior to E6005 treatment was identified as the clinical parameter influenced to M11 detection with statistical significance (p = .003). M11 detection was not clearly associated with the incidence of adverse events occurred.Conclusion: Exposure to topical E6005 is associated with the eczema-associated area, however, that is not distinctly associated with its adverse drug reactions occurred after drug applications possibly due to E6005’s characteristics of tissue distribution.

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 score0.018
Threshold uncertainty score0.341

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 head0.011
GPT teacher head0.271
Teacher spread0.259 · 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
Published2018
Admission routes1
Has abstractyes

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