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The Discontinuation and Effectiveness of Sequential Advanced Therapy in Rheumatoid Arthritis: Real-World Data

2025· article· en· W6966488248 on OpenAlexaffvenueabout

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity of TorontoUniversity of OttawaSinai Health SystemOttawa HospitalUniversity Health Network
Fundersnot available
KeywordsDiscontinuationRheumatoid arthritisObservational studyCohortCohort studyPharmacotherapyDiseaseRetrospective cohort study

Abstract

fetched live from OpenAlex

Objectives Patients with rheumatoid arthritis (RA) who fail conventional synthetic treatment with disease modifying antirheumatic drugs (csDMARDs) are eligible for biological DMARDs (bDMARDs) or targeted synthetic DMARDs (tsDMARDs). Many patients experience a lack of response or intolerance to their first advanced therapy (AT), requiring a change in medication. Subsequent treatment choice is important for achieving successful long-term disease control. The current study aimed to describe the pattern of sequential AT use in RA patients in a multicentre observational cohort and to evaluate the survival rate and effectiveness of each line of therapy. Methods Adult RA patients participating in the Ontario Best Practice Research Initiative (OBRI) and initiating their first AT (line 1) between Jun. 1, 2008, and Jan. 1, 2023, were included. Drug retention was defined as the time from initiation to discontinuation of therapy (due to any reason). We evaluated effectiveness using Clinical Disease Activity Index (CDAI) change, the proportion of patients reaching the minimally clinically important difference (MCID), CDAI low disease activity (LDA), and remission at 6 months. Time to event analysis was used for treatment discontinuation and general linear mix model for effectiveness. An exploratory analysis compared outcomes in patients who started their first AT before and after 2010, the year treat to target guidelines were published. We also compared drug survival of the first AT in 3 therapeutic groups (TNFi, non-TNFi, tsDMARDs). Results A total of 2449 patients were included (line 1=1117, line 2=679, line 3=339, and lines 4 to 7=314). TNFi was predominantly used as first-line AT, with Etanercept and Adalimumab being the 1st and 2nd most common choices. Subsequent AT lines exhibited lower TNFi usage. Risk of discontinuation increased in later lines (Figure 1). Persisting after adjustments for confounders. Pre-2010 and post-2010 cohorts displayed significant differences in first-line AT retention, suggesting quicker switches post-2010 (Median survival 12.2 vs 7.6 years). Efficacy outcomes favored first-line AT, with lower CDAI change and attainment of clinical targets in subsequent lines. Conclusion We found that TNFi remains the most common first AT, however, there has been a downward trend in using TNFi. The first AT has longer survival and better efficacy when compared to subsequent lines. Clinicians tend to switch the first-line therapy earlier since 2010, likely due to a shift toward a treat to target approach and more available therapeutic options.

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)0.033
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 score0.022
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.020
GPT teacher head0.332
Teacher spread0.311 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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