Unmet Needs in Spondyloarthritis: Pathogenesis, Clinical Trial Design, and Nonpharmacologic Therapy
Bibliographic record
Abstract
A program focused on pathogenesis, clinical trial design, and nonpharmacologic mind-body therapy for spondyloarthritis (SpA) was presented at the Spondylitis Association of America Unmet Needs Conference IV. SpA pathogenesis is incompletely understood but involves a complex set of drivers, including genetics, biomechanical stress, and microbial factors. Affected tissues may include axial and peripheral joints, entheses, skin, uvea, and intestines. The specific role of key cytokines like interleukin (IL)-23, IL-17, and tumor necrosis factor in the phases of this inflammatory process remains unclear. New insights into pathogenesis will continue to generate targets for novel therapeutics. How to optimally evaluate those therapeutics in clinical trials, and for the various manifestations of SpA, remains less clear. Future trials need better generalizability, robust subgroup analyses to assess differential responses for distinct disease manifestations, a focus on comparative efficacy, and outcomes relevant to the clinician and the patient. Additionally, study designs need to leverage available technology to facilitate subject participation in trials. In view of the interplay between biologic, physical, and psychological aspects of disease, there is increasing attention to nonpharmacologic agents, with the aim of maximizing long-term health-related quality of life through the control of symptoms and inflammation. Recent studies provide encouraging evidence that mind-body interventions such as tai chi, qigong, yoga, and meditation have benefits for patients with SpA, particularly those with pain. The advances in our understanding of pathogenesis, novel therapeutics, and nonpharmacologic interventions have revolutionized the management of SpA, but numerous questions around optimal management remain.
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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 | 0.525 | 0.425 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.018 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".