Predictors of Loss of Remission and Disease Flares in Patients with Axial Spondyloarthritis Receiving Antitumor Necrosis Factor Treatment: A Retrospective Study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate rate and predictive factors of loss of remission and disease flare in patients with axial spondyloarthritis (axSpA) receiving antitumor necrosis factor (anti-TNF) treatment. METHODS: In this retrospective multicenter study, patients with axSpA, according to the Assessment of Spondyloarthritis international Society (ASAS) criteria, treated with adalimumab, etanercept, or infliximab with a minimum followup of 12 months and satisfying the ASAS partial remission criteria and/or Ankylosing Spondylitis Disease Activity Score (ASDAS) inactive disease were studied. Disease flare was defined as a Bath Ankylosing Spondylitis Disease Activity Index score > 4.5 or ASDAS score > 2.5 on at least 1 occasion. RESULTS: One hundred seventy-four patients with axSpA were studied. After a median [interquartile range (IQR)] followup of 4 years (2-6), 37 patients (21.2%) experienced a loss of remission and 28 (16.1% of the whole study group) a disease flare. Median (IQR) duration of remission in patients who lost this status was 1 year (0.625-2). Higher median erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) values, continuous nonsteroidal antiinflammatory drug (NSAID) use, and an ASDAS-CRP ≥ 0.8 during the remission period were significantly associated with both loss of remission and disease flare. At the multivariate analysis, continuous NSAID intake (OR 4.05, 95% CI 1.4-11.74, p = 0.010) and ESR > 15 (OR 2.90, 95% CI 1.23-6.82, p = 0.015) were the only factors predictive of disease reactivation. CONCLUSION: In this study, loss of remission and disease flares occurred, respectively, in about 21% and 16% of the patients with axSpA who achieved a state of remission while receiving anti-TNF therapy. Residual disease activity was associated with disease reactivation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".