Targeting the Interleukin-23/Interleukin-17 Inflammatory Pathway: Successes and Failures in the Treatment of Axial Spondyloarthritis
Bibliographic record
Abstract
The IL-23/IL-17 pathway has been implicated in the etiopathogenesis of axial spondyloarthritis through studies of genetic polymorphisms associated with disease, an animal model with over-expression of IL-23 that resembles human disease, and observations that cytokines in this pathway can be found at the site of disease in both humans and animal models. However, the most direct evidence has emerged from clinical trials of agents targeting cytokines in this pathway. Monoclonal antibodies targeting IL-17A have been shown to ameliorate signs and symptoms, as well as MRI inflammation in the spine and sacroiliac joints, in patients with radiographic and non-radiographic axial spondyloarthritis. This was evident in patients refractory to non-steroidal anti-inflammatory agents as well as patients failing treatment with tumor necrosis factor inhibitor therapies. Treatment with a bispecific antibody targeting both IL-17A and IL-17F was also effective in a phase II study. Post-hoc analyses have even suggested a potential disease-modifying effect in reducing development of spinal ankylosis. However, benefits for extra-articular manifestations were limited to psoriasis and did not extend to colitis and uveitis. Conversely, trials of therapies targeting IL-23 did not demonstrate any significant impact on signs, symptoms, and MRI inflammation in axial spondyloarthritis. These developments coincide with recent observations that expression of these cytokines is evident in many different cell types with roles in innate as well as adaptive immunity. Moreover, evidence has emerged for the existence of both IL-23-dependent and IL-23-independent pathways regulating expression of IL-17, potentially associated with different roles in intestinal and axial skeletal inflammation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".