Persistence to Biologic Therapy Among Patients With Ankylosing Spondylitis: An Observational Study Using the OPAL Dataset
Bibliographic record
Abstract
OBJECTIVE: To describe the treatment response and persistence to biologic disease-modifying antirheumatic drug (bDMARD) therapy in patients with ankylosing spondylitis (AS) in a real-world Australian cohort. METHODS: This was a retrospective, noninterventional cohort study that extracted data for patients with AS from the Optimising Patient outcomes in Australian RheumatoLogy (OPAL) dataset for the period of August 2006 to September 2019. Patients were classified as either bDMARD initiators if they commenced a bDMARD during the sampling window, or bDMARD-naïve if they did not. Results were summarized descriptively. Treatment persistence was calculated using Kaplan-Meier methods. Differences in treatment persistence were explored using log-rank tests. RESULTS: There were 5048 patients with AS identified. Of these, 2597 patients initiated bDMARDs and 2451 remained bDMARD-naïve throughout the study window. Treatment with first-, second-, and third-line bDMARDs significantly reduced disease activity. Median persistence on first-line bDMARDs was 96 months (95% CI 85-109), declining to 19 months (95% CI 16-22) in second-line therapy, and 15 months (95% CI 11-18) in third-line therapy. Median persistence was longest for the golimumab (GOL) group in all lines of therapy and shortest for the etanercept (ETN) group. Differences in persistence rates according to the time period that bDMARDs were prescribed (pre- and post-2012) were also seen for ETN and adalimumab. CONCLUSION: In this cohort, all bDMARDs effectively reduced AS disease activity. Treatment persistence was sustained for up to 8 years for patients remaining on their first bDMARD, longer than on subsequent agents. Further research is needed to determine its influence on treatment recommendations.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".