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Record W2343934601 · doi:10.3899/jrheum.151290

Comparison of Etanercept Monotherapy and Combination Therapy with Methotrexate in Psoriatic Arthritis: Results from 2 Clinical Trials

2016· article· en· W2343934601 on OpenAlexvenueno aff
Bernard Combe, Frank Behrens, Neil McHugh, F Brock, Urs Kerkmann, Blerina Kola, Gaia Gallo

Bibliographic record

VenueThe Journal of Rheumatology · 2016
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
FundersPfizer
KeywordsMedicineEtanerceptPsoriatic arthritisMethotrexateInternal medicinePsoriasisCombination therapyRheumatoid arthritisRheumatologyPlaceboClinical trialPsoriasis Area and Severity IndexOncologyPhysical therapyDermatologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the clinical/functional outcomes associated with etanercept (ETN) monotherapy versus combination therapy in psoriatic arthritis (PsA). METHODS: Data from patients with PsA who received ETN alone (n = 322) or combined with methotrexate (MTX; n = 152) for 24 weeks in 2 placebo-controlled clinical trials were summarized across studies. RESULTS: Similar proportions of patients in the monotherapy and combination therapy groups achieved the PsA Response Criteria (80% and 83%) and the American College of Rheumatology improvements of 20% (ACR20; both 70%); numerically higher proportions receiving monotherapy achieved ACR50 (55% vs 48%) and ACR70 (35% vs 27%). Little between-group difference was observed in the 28-joint Disease Activity Score with C-reactive protein, the Psoriasis Area and Severity Index, and the Health Assessment Questionnaire-Disability Index improvement. CONCLUSION: ETN with and without MTX provided similar benefits in active PsA.

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)0.010
metaresearch head score (Gemma)0.012
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 score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
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 head0.109
GPT teacher head0.424
Teacher spread0.315 · 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

Citations37
Published2016
Admission routes1
Has abstractyes

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