Latest Developments in Imaging for Axial Disease in Psoriatic Arthritis
Bibliographic record
Abstract
Axial disease in psoriatic arthritis (axPsA), affecting the sacroiliac joints (SIJ) and spine, is recognized as one of the domains in the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendations for psoriatic arthritis (PsA). Accurate recognition of this manifestation is crucial for comprehensive management of this disease. It is defined according to both clinical and imaging features. Clinically, inflammatory back pain (IBP) is a key feature; however, findings from a recent Canadian inception cohort study—Screening for Axial Spondyloarthritis in Psoriasis, Iritis, or Colitis Cohorts 1 and 2 (SASPIC1 and 2)—which included patients with psoriasis and undiagnosed back pain, showed no differences in the frequency of IBP or non-steroidal anti-inflammatory drug (NSAID) responsiveness between those diagnosed with axPsA and individuals with other causes of chronic back pain. Similarly, data from the global Axial Involvement in Psoriatic Arthritis (AXIS) cohort revealed only minor numerical differences in NSAID responsiveness or frequency of IBP, according to the ASAS criteria, between participants with and without axial involvement when evaluated by central reviewers. Recent post-hoc studies of clinical trials in PsA have attempted to identify axPsA according to a Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) threshold of ≥4. However, MRI-based assessment of axPsA in a large European cohort of 581 PsA patients, recruited across 17 European registries within the EuroSpA network, indicated that a BASDAI ≥4 did not discriminate PsA patients with axial disease from those without. Moreover, only 25–45% of patients with radiographic features of axPsA have been reported to have IBP, with some patients being clinically perceived as asymptomatic. Additionally, axSpA-based IBP criteria have demonstrated limited specificity for axPsA. Studies using MRI have reported poor correlation between sacroiliitis on imaging and both the presence and type of back pain.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".