American College of Rheumatology/Spondylitis Association of America/Spondyloarthritis Research and Treatment Network 2015 Recommendations for the Treatment of Ankylosing Spondylitis and Nonradiographic Axial Spondyloarthritis
Bibliographic record
Abstract
OBJECTIVE: To provide evidence-based recommendations for the treatment of patients with ankylosing spondylitis (AS) and nonradiographic axial spondyloarthritis (SpA). METHODS: A core group led the development of the recommendations, starting with the treatment questions. A literature review group conducted systematic literature reviews of studies that addressed 57 specific treatment questions, based on searches conducted in OVID Medline (1946-2014), PubMed (1966-2014), and the Cochrane Library. We assessed the quality of evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) method. A separate voting group reviewed the evidence and voted on recommendations for each question using the GRADE framework. RESULTS: In patients with active AS, the strong recommendations included use of nonsteroidal antiinflammatory drugs (NSAIDs), use of tumor necrosis factor inhibitors (TNFi) when activity persists despite NSAID treatment, not to use systemic glucocorticoids, use of physical therapy, and use of hip arthroplasty for patients with advanced hip arthritis. Among the conditional recommendations was that no particular TNFi was preferred except in patients with concomitant inflammatory bowel disease or recurrent iritis, in whom TNFi monoclonal antibodies should be used. In patients with active nonradiographic axial SpA despite treatment with NSAIDs, we conditionally recommend treatment with TNFi. Other recommendations for patients with nonradiographic axial SpA were based on indirect evidence and were the same as for patients with AS. CONCLUSION: These recommendations provide guidance for the management of common clinical questions in AS and nonradiographic axial SpA. Additional research on optimal medication management over time, disease monitoring, and preventive care is needed to help establish best practices in these areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".