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Effects of etanercept therapy on fatigue and symptoms of depression in subjects treated for moderate to severe plaque psoriasis for up to 96 weeks

2007· letter· en· W1979000113 on OpenAlexaff
Ranga Krishnan, David Cella, C. Leonardi, Kim Papp, Alice B. Gottlieb, M. Dunn, C.F. Chiou, Vaishali Patel, Angelika Jahreis

Bibliographic record

VenueBritish Journal of Dermatology · 2007
Typeletter
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsProbity Medical Research
Fundersnot available
KeywordsEtanerceptMedicinePsoriasisPlaceboInternal medicineDepression (economics)Randomized controlled trialClinical trialTumor necrosis factor alphaDermatologyPathologyAlternative medicine

Abstract

fetched live from OpenAlex

Conflicts of interest: see Acknowledgments. Trial registration: This study is registered with ClinicalTrials.gov with the identifier NCT00111449. Sir, Fatigue and depression have been associated with psoriasis.1, 2 Proinflammatory cytokines such as tumour necrosis factor (TNF), implicated in the pathogenesis of psoriasis, also have been linked to symptoms of fatigue3 and depression.4 Etanercept is a soluble TNF receptor‐Fc fusion protein that has U.S. Food and Drug Administration approval for the treatment of moderate to severe plaque psoriasis. Results have been reported previously of a 12‐week, randomized, double‐blind trial of etanercept or placebo in psoriasis.5 Herein, we report the longer‐term results from this study. After week 12, 591 subjects (95% of enrolled subjects) entered a second portion of the study in which all received open‐label etanercept 50 mg twice weekly. Of these, 233 subjects (77%) from the etanercept/etanercept group and 231 subjects (81%) from the placebo/etanercept group completed 84 weeks of open‐label etanercept.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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 designNon-randomized trial
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

Citations120
Published2007
Admission routes1
Has abstractyes

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Same venueBritish Journal of DermatologySame topicPsoriasis: Treatment and PathogenesisFrench-language works237,207