Impact of disease manifestations on first biologic drug survival in axial spondyloarthritis: a real-life Canadian study
Bibliographic record
Abstract
Objectives: The primary objective of this study was to assess the impact of extramusculoskeletal manifestations (EMMs) and peripheral musculoskeletal features on first biologic drug survival in subjects with axial spondyloarthritis (axSpA). The secondary objective was to evaluate the impact of reasons for treatment discontinuation. Methods: A total of 593 axSpA patients from the SpondyloArthritis Research Consortium of Canada initiating a first biologic drug were identified between 2003 and 2023. Drug survival was presented using Kaplan-Meier curves for each disease manifestation and compared using the logrank test. A Cox proportional hazards model was used to analyse independent predictors of discontinuation. The impact of reasons for treatment discontinuation was assessed using a competing risk analysis. Results: The presence of psoriasis, nail psoriasis, dactylitis, at least one EMM or at least one peripheral musculoskeletal manifestation was associated with prolonged drug survival compared with subjects without these disease manifestations. In multivariable analysis, psoriasis [hazard ratio (HR) 0.53 (95% CI 0.33, 0.86)] and at least one peripheral musculoskeletal manifestation [HR 0.65 (95% CI 0.47, 0.92)] were independently associated with a lower risk for biologic discontinuation. The presence of psoriasis or dactylitis was associated with reduced treatment discontinuation in patients who stopped their biologic medication for ineffectiveness but not when treatment was discontinued due to adverse events. Conclusions: This study showed that the presence of some axSpA disease manifestations were associated with prolonged biologic drug survival. Psoriasis and peripheral musculoskeletal manifestations were the most significant predictors of treatment retention. Future research will be needed to further refine treatment strategies according to specific disease manifestations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".