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Record W2970140635 · doi:10.3899/jrheum.190299

Comparative Persistence of Methotrexate and Tumor Necrosis Factor Inhibitors in Rheumatoid Arthritis, Psoriatic Arthritis, and Ankylosing Spondylitis

2019· article· en· W2970140635 on OpenAlexvenueno aff
Michael George, Joshua F. Baker, Alexis Ogdie

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesUniversity of PennsylvaniaRheumatology Research FoundationClinical Science Research and DevelopmentNational Institutes of HealthPfizerU.S. Department of Veterans Affairs
KeywordsMedicinePsoriatic arthritisRheumatoid arthritisConcomitantAnkylosing spondylitisDiscontinuationInternal medicineAdalimumabMethotrexateGolimumabInfliximabProportional hazards modelEtanerceptCohortRetrospective cohort studyOncologyTumor necrosis factor alpha

Abstract

fetched live from OpenAlex

OBJECTIVE: The role of methotrexate (MTX) for the treatment of spondyloarthritis (SpA) remains uncertain. Aims were to compare MTX and tumor necrosis factor inhibitor (TNFi) persistence in spondyloarthritis versus rheumatoid arthritis (RA) and to determine whether concomitant conventional synthetic disease-modifying antirheumatic drug (csDMARD) use is associated with improved TNFi persistence in SpA. METHODS: This retrospective cohort study using Optum's deidentified Clinformatics Data Mart Database 2000-2014 identified patients with RA, psoriatic arthritis (PsA), and ankylosing spondylitis (AS) without prior biologic use who were initiating MTX or a TNFi. Cox proportional hazards models compared time to medication discontinuation over the next 2 years between patients with RA, PsA, or AS, adjusting for potential confounders. In similar analyses stratified by disease, Cox models were used to assess whether concomitant use of csDMARD was associated with TNFi persistence. RESULTS: We identified 31,527 MTX initiators (26,708 RA, 2939 PsA, 1880 AS) and 34,651 TNFi initiators (24,134 RA, 6705 PsA, 3812 AS). MTX was discontinued sooner in patients with PsA [adjusted HR (aHR) 1.10, 95% CI 1.04-1.16] and AS (aHR 1.23, 1.16-1.31) versus RA, while TNFi were discontinued at similar rates in RA and AS and discontinued later in PsA (aHR 0.93, 0.89-0.97). Concomitant use of MTX (compared to no csDMARD) was associated with lower rates of TNFi discontinuation in RA (aHR 0.85, 0.80-0.89), PsA (aHR 0.81, 0.74-0.89), and AS (aHR 0.79, 0.67-0.93). CONCLUSION: MTX discontinuation occurs sooner in patients with PsA and AS versus RA. Concomitant use of MTX with a TNFi, however, is associated with improved TNFi persistence in all 3 diseases.

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)0.002
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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".

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Citations32
Published2019
Admission routes1
Has abstractyes

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